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Alleviating linear ecological bias and optimal design with subsample data

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  • Adam N. Glynn
  • Jon Wakefield
  • Mark S. Handcock
  • Thomas S. Richardson

Abstract

Summary. We illustrate that combining ecological data with subsample data in situations in which a linear model is appropriate provides two main benefits. First, by including the individual level subsample data, the biases that are associated with linear ecological inference can be eliminated. Second, available ecological data can be used to design optimal subsampling schemes that maximize information about parameters. We present an application of this methodology to the classic problem of estimating the effect of a college degree on wages, showing that small, optimally chosen subsamples can be combined with ecological data to generate precise estimates relative to a simple random subsample.

Suggested Citation

  • Adam N. Glynn & Jon Wakefield & Mark S. Handcock & Thomas S. Richardson, 2008. "Alleviating linear ecological bias and optimal design with subsample data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 179-202, January.
    • Handle: RePEc:bla:jorssa:v:171:y:2008:i:1:p:179-202
    DOI: 10.1111/j.1467-985X.2007.00511.x
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    References listed on IDEAS

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    1. Judith K. Hellerstein & Guido W. Imbens, 1999. "Imposing Moment Restrictions From Auxiliary Data By Weighting," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 1-14, February.
    2. Trivellore E. Raghunathan & Paula K. Diehr & Allen D. Cheadle, 2003. "Combining Aggregate and Individual Level Data to Estimate an Individual Level Correlation Coefficient," Journal of Educational and Behavioral Statistics, , vol. 28(1), pages 1-19, March.
    3. Guido W. Imbens & Tony Lancaster, 1994. "Combining Micro and Macro Data in Microeconometric Models," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 655-680.
    4. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
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    Cited by:

    1. Irene L. Hudson & Linda Moore & Eric J. Beh & David G. Steel, 2010. "Ecological inference techniques: an empirical evaluation using data describing gender and voter turnout at New Zealand elections, 1893–1919," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 185-213, January.
    2. Michael C. Herron & Kevin M. Quinn, 2016. "A Careful Look at Modern Case Selection Methods," Sociological Methods & Research, , vol. 45(3), pages 458-492, August.

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