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The Evaluation of Community-Based Interventions: Group Randomization, Limits and Alternatives

Author

Listed:
  • Schmidt, Christoph M.

    (RWI)

  • Baltussen, Rob

    (affiliation not available)

  • Sauerborn, Rainer

    (Heidelberg University)

Abstract

The context of community-based interventions presents formidable problems for any evaluation analysis. Group-randomized studies do possess ideal properties in theory, but in practice, group- randomization might not be a feasible alternative at all or group-randomized studies might be contaminated. Thus, the decisive advantage of randomized controlled trials, that they and only they provide for a completely convincing identification strategy in the presence of observable and unobservable confounders, is lost. There are alternative strategies for the identification of treatment effects also in the case of unobservable confounders, however, although they specifically require unverifiable a priori information to be available. Moreover, when using non- experimental data, one can often extend sample size at low cost, and thus estimate parameters very precisely; therefore, for any particular situation the relative attractiveness of experimental and non-experimental approaches should be explored.

Suggested Citation

  • Schmidt, Christoph M. & Baltussen, Rob & Sauerborn, Rainer, 2000. "The Evaluation of Community-Based Interventions: Group Randomization, Limits and Alternatives," IZA Discussion Papers 206, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp206
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    References listed on IDEAS

    as
    1. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    2. Altman, David G., 1986. "A framework for evaluating community-based heart disease prevention programs," Social Science & Medicine, Elsevier, vol. 22(4), pages 479-487, January.
    3. Joshua D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
    4. Heckman, James J, 1996. "Randomization as an Instrumental Variable: Notes," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 336-341, May.
    5. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
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    Cited by:

    1. Christoph M. Schmidt, 2000. "Arbeitsmarktpolitische Massnahmen und ihre Evaluierung: eine Bestandsaufnahme," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 69(3), pages 425-437.

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    More about this item

    Keywords

    Randomized controlled trials; self-selection; econometric evaluation; observational studies;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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