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Estimation of dyadic characteristics of family networks using sample survey data

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Listed:
  • Skinner, Chris J.
  • Steele, Fiona

Abstract

We consider the use of sample survey data to estimate dyadic characteristics of family networks, with an application to noncoresident parent–child dyads. We suppose that survey respondents report either from a parent or child perspective about a dyad, depending on their membership of the dyad. We construct separate estimators of common dyadic characteristics using data from both a parent and a child perspective and show how comparisons of these estimators can shed light on data quality issues including differential missingness and reporting error. In our application we find that a simple missingness model explains some striking patterns of discrepancies between the estimators and consider the use of poststratification and a related redefinition of count variables to adjust for these discrepancies. We also develop approaches to combining the separate estimators efficiently to estimate means and frequency distributions within subpopulations.

Suggested Citation

  • Skinner, Chris J. & Steele, Fiona, 2020. "Estimation of dyadic characteristics of family networks using sample survey data," LSE Research Online Documents on Economics 102338, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:102338
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    File URL: http://eprints.lse.ac.uk/102338/
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    References listed on IDEAS

    as
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    3. Altonji, Joseph G & Hayashi, Fumio & Kotlikoff, Laurence J, 1997. "Parental Altruism and Inter Vivos Transfers: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 105(6), pages 1121-1166, December.
    4. Michael Rendall & Lynda Clarke & H. Peters & Nalini Ranjit & Georgia Verropoulou, 1999. "Incomplete reporting of men’s fertility in the united states and britain: A research note," Demography, Springer;Population Association of America (PAA), vol. 36(1), pages 135-144, February.
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    More about this item

    Keywords

    coresident; network sampling; poststratification; reporting error;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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