IDEAS home Printed from https://ideas.repec.org/p/mpg/wpaper/2019_01.html

Estimating Heterogeneous Reactions to Experimental Treatments

Author

Listed:
  • Christoph Engel

    (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.

Suggested Citation

  • Christoph Engel, 2019. "Estimating Heterogeneous Reactions to Experimental Treatments," Discussion Paper Series of the Max Planck Institute for Behavioral Economics 2019_01, Max Planck Institute for Behavioral Economics.
  • Handle: RePEc:mpg:wpaper:2019_01
    as

    Download full text from publisher

    File URL: http://www.coll.mpg.de/pdf_dat/2019_01online.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Orland, Andreas & Rostam-Afschar, Davud, 2021. "Flexible work arrangements and precautionary behavior: Theory and experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 442-481.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mpg:wpaper:2019_01. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marc Martin (email available below). General contact details of provider: https://edirc.repec.org/data/mppggde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.