Estimating Heterogeneous Reactions to Experimental Treatments

Christoph Engel

No 2019_01, Discussion Paper Series of the Max Planck Institute for Research on Collective Goods from Max Planck Institute for Research on Collective Goods

Abstract: Frequently in experiments there is not only variance in the reaction of participants to treatment. The heterogeneity is patterned: discernible types of participants react differently. In principle, a finite mixture model is well suited to simultaneously estimate the probability that a given participant belongs to a certain type, and the reaction of this type to treatment. Yet often, finite mixture models need more data than the experiment provides. The approach requires ex ante knowledge about the number of types. Finite mixture models are hard to estimate for panel data, which is what experiments often generate. For repeated experiments, this paper offers a simple two-step alternative that is much less data hungry, that allows to find the number of types in the data, and that allows for the estimation of panel data models. It combines machine learning methods with classic frequentist statistics.

Keywords: heterogeneous treatment effect; finite mixture model; panel data; two-step approach; machine learning; CART (search for similar items in EconPapers)
JEL-codes: C14 C23 C91 (search for similar items in EconPapers)
Date: 2019-01
New Economics Papers: this item is included in nep-big, nep-ecm and nep-exp
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.coll.mpg.de/pdf_dat/2019_01online.pdf (application/pdf)

Related works:
Journal Article: Estimating heterogeneous reactions to experimental treatments (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mpg:wpaper:2019_01

Access Statistics for this paper

More papers in Discussion Paper Series of the Max Planck Institute for Research on Collective Goods from Max Planck Institute for Research on Collective Goods Contact information at EDIRC.
Bibliographic data for series maintained by Marc Martin ().