Data and Code for: Using Models to Persuade

Version
V0
Resource Type
Dataset
Creator
  • Schwartzstein, Joshua (Harvard Business School)
  • Sunderam, Adi (Harvard Business School)
Publication Date
2020-12-17
Description
  • Abstract

    We present a framework where “model persuaders” influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model persuaders face a tradeoff: better-fitting models induce less movement in receivers’ beliefs. Consequently, a receiver exposed to the true model can be most misled by persuasion when that model fits poorly, competition between persuaders tends to neutralize the data by pushing towards better-fitting models, and a persuader facing multiple receivers is more effective when he can send tailored, private messages.
Temporal Coverage
  • 1949-01-01 / 2018-12-31
    Time Period: Sat Jan 01 00:00:00 EST 1949--Mon Dec 31 00:00:00 EST 2018 (Good to Great)
  • 2019-01-08 / 2019-01-28
    Time Period: Tue Jan 08 00:00:00 EST 2019--Mon Jan 28 00:00:00 EST 2019 (Technical Analysis)
Availability
Download
This study is freely available to the general public via web download.
Relations
  • Has version
    DOI: 10.3886/E120507V1
Publications
  • Schwartzstein, Joshua, and Adi Sunderam. “Using Models to Persuade.” American Economic Review, n.d.

Update Metadata: 2020-12-17 | Issue Number: 1 | Registration Date: 2020-12-17