The Evaluation of Community-Based Interventions: A Monte Carlo Study
Boris Augurzky () and
No 270, IZA Discussion Papers from Institute of Labor Economics (IZA)
The evaluation of interventions such as active labor market policies or medical programs by means of a randomized controlled trial is often considered the gold standard. However, randomized experiments might face severe shortcomings especially if performed at the group level. One such problem is caused by small sample size which might prevent the experiment from developing its fundamental virtue in balancing all relevant covariates. This paper investigates the potential and limits of experimental and non-experimental approaches to the evaluation problem, in particular the use of instrumental variables, in a numerical simulation study, against the particular background of community-based interventions. In our simulations, we emphasize the trade-off between bias and precision by imposing a smaller number of communities whenever we model a randomized experiment, and by allowing for a correspondingly larger number of communities in all cases where selection into the program is not controlled completely by the analyst.
Keywords: Grouped data; observational study; randomized experiment; simulation study (search for similar items in EconPapers)
JEL-codes: C15 H43 (search for similar items in EconPapers)
Pages: 36 pages
References: Add references at CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp270
Ordering information: This working paper can be ordered from
IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Access Statistics for this paper
More papers in IZA Discussion Papers from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Holger Hinte ().