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Selection Bias Adjustment in Treatment-Effect Models as a Method of Aggregation


  • Robert A. Moffitt


The aim of this note is to interpret estimation of the conventional treatment-effect selection-bias model in econometrics as a method of aggregation and to draw the implications of this interpretation. In addition, the paper notes the connection of this interpretation with an older style of analysis using grouped data and illustrates the aggregation analogy with examples from the literature. The estimation technique used to illustrate the points is the method of instrumental variables.

Suggested Citation

  • Robert A. Moffitt, 1996. "Selection Bias Adjustment in Treatment-Effect Models as a Method of Aggregation," NBER Technical Working Papers 0187, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0187 Note: PE

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    References listed on IDEAS

    1. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
    2. repec:mpr:mprres:1508 is not listed on IDEAS
    3. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
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    Cited by:

    1. Joyce, Theodore, 1999. "Impact of augmented prenatal care on birth outcomes of Medicaid recipients in New York City," Journal of Health Economics, Elsevier, vol. 18(1), pages 31-67, January.
    2. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, Social Science Research Center Berlin (WZB).

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    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables


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