MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Learning from each other: causal inference and American political development

Author(s)
Jenkins, Jeffery A.; McCarty, Nolan; Stewart III, Charles H
Thumbnail
Download11127_2019_728_ReferencePDF.pdf (389.3Kb)
Open Access Policy

Open Access Policy

Creative Commons Attribution-Noncommercial-Share Alike

Terms of use
Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
Metadata
Show full item record
Abstract
Within political science, a movement focused on increasing the credibility of causal inferences (CIs) has gained considerable traction in recent years. While CI has been incorporated extensively into most disciplinary subfields, it has not been applied often in the study of American political development (APD). This special issue considers ways in which scholars of CI and APD can engage in mutually beneficial ways to produce better overall research. As the contributions to the symposium demonstrate, clear scientific gains are to be had from greater CI–APD engagement.
Date issued
2019-11
URI
https://hdl.handle.net/1721.1/128274
Department
Massachusetts Institute of Technology. Department of Political Science
Journal
Public Choice
Publisher
Springer Science and Business Media LLC
Citation
Jenkins, Jeffery A. et al. "Learning from each other: causal inference and American political development." Public Choice 185, 3-4 (November 2019): 245–251 © 2019 Springer Science Business Media, LLC, part of Springer Nature
Version: Author's final manuscript
ISSN
0048-5829
1573-7101

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.