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Estimating the Intergenerational Correlation of Incomes: An Errors in Variables Framework

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  • Ramses H. Abul Naga

Abstract

The estimation of the intergenerational correlation of incomes is usually carried out by proxying permanent incomes using suitable indicators of economic status, and by treating the resulting measurement error problem using averaging or instrumenting procedures. Here we take the permanent income of the parents' family to be unobserved, but we assume that its determinants are known to the researcher. A two-stage procedure as well as a MIMIC type covariance estimator applied to a US sample of parents and children entail estimates of the order of 0.61 to 0.64 for the coefficient of intergenerational income transmission. OLS estimates this parameter at 0.5. The variance ratio of permanent to total income is also estimated to be in the range of 0.77 to 0.8, implying a correction factor of 1.25 to 1.3 for OLS estimates.

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  • Ramses H. Abul Naga, 1999. "Estimating the Intergenerational Correlation of Incomes: An Errors in Variables Framework," STICERD - Distributional Analysis Research Programme Papers 44, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stidar:44
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    1. Ramses H. ABUL NAGA, 2001. "Biases of the Ordinary Least Squares and Instrumental Variables Estimators of the Intergenerational Earnings Correlation : Revisited in the Light of Panel Data," Cahiers de Recherches Economiques du Département d'économie 01.05, Université de Lausanne, Faculté des HEC, Département d’économie.
    2. Ramses ABUL NAGA & Jaya KRISHNAKUMAR, 1999. "Panel Data Estimation of the Intergenerational Correlation of Incomes," Cahiers de Recherches Economiques du Département d'économie 9910, Université de Lausanne, Faculté des HEC, Département d’économie.
    3. Ramses Abul Naga, 2008. "Biases of the ordinary least squares and instrumental variables estimators of the intergenerational earnings elasticity: Revisited in the light of panel data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(4), pages 323-350, December.
    4. Markus Jäntti & Stephen P. Jenkins, 2013. "Income Mobility," SOEPpapers on Multidisciplinary Panel Data Research 607, DIW Berlin, The German Socio-Economic Panel (SOEP).
    5. Lindquist, Matthew J. & Böhlmark, Anders, 2005. "Life-Cycle Variations in the Association between Current and Lifetime Income: Country, Cohort and Gender Comparisons," Working Paper Series 4/2005, Stockholm University, Swedish Institute for Social Research.
    6. Sari Pekkala & Robert E. B. Lucas, 2004. "On the Importance of Finnishing School: Half a Century of Inter-Generational Economic Mobility in Finland," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-141, Boston University - Department of Economics.
    7. Nilsson, William, 2005. "Opportunities, Preferences and Incomes," Umeå Economic Studies 649, Umeå University, Department of Economics.
    8. Donal O’Neill & Olive Sweetman & Dirk Van de gaer, 2007. "The effects of measurement error and omitted variables when using transition matrices to measure intergenerational mobility," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(2), pages 159-178, August.

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    More about this item

    Keywords

    Intergenerational mobility; errors in variables;

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

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