Programme Evaluation with Multiple Treatments
AbstractThis paper reviews the main identification and estimation strategies for microeconometric policy evaluation. Particular emphasis is laid on evaluating policies consisting of multiple programmes, which is of high relevance in practice. For example, active labour market policies may consist of different training programmes, employment programmes and wage subsidies. Similarly, sickness rehabilitation policies often offer different vocational as well as non-vocational rehabilitation measures. First, the main identification strategies "control-for-confounding-variables, difference-in-difference, instrumental-variable, and regression-discontinuity identification" are discussed in the multiple-programme setting. Thereafter, the different nonparametric matching and weighting estimators of the average treatment effects and their properties are examined. Copyright Blackwell Publishers Ltd, 2004.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Economic Surveys.
Volume (Year): 18 (2004)
Issue (Month): 2 (04)
Contact details of provider:
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0950-0804
Other versions of this item:
- Markus Froelich, 2002. "Programme Evaluation with Multiple Treatments," University of St. Gallen Department of Economics working paper series 2002 2002-17, Department of Economics, University of St. Gallen.
- Frölich, Markus, 2002. "Programme Evaluation with Multiple Treatments," IZA Discussion Papers 542, Institute for the Study of Labor (IZA).
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.