NYU Politics Data Center

16th Annual Northeast Political Methodology Meeting at NYU

Registration closes Monday, April 18, 2016.


All events take place at the NYU Politics Department, Room 217.

19 W 4th Street, 2nd Floor (Get Google Maps directions here)

(Corner of W 4th Street and Mercer Street)


Friday, April 29, 2016


11:30 - 12:30:  Lunch


12:30 - 02:00:  Dan Hopkins

 Dept of Political Science, Univ of Pennsylvania

 "The Exaggerated Life of Death Panels: Using Text to Understand the Limits of Framing Effects in the Health Care Debate."

                          [Abstract]Experiments demonstrate that framing can influence public opinion under certain conditions. Yet outside the laboratory or survey setting, additional constraints might further limit elites' ability to reshape public opinion through framing. The 2009-12 health care debate provides an unparalleled opportunity to observe the interplay of elite rhetoric and public opinion in real-world conditions. This paper couples automated content analyses with survey data from 30,370 Americans to better measure elite frames, public opinion, and their relationship. Multiple empirical tests uncover only limited evidence of framing effects during the debate. While the frames employed by political elites are punctuated, mass attitudes are not. The very language Americans use to explain their opinions proves stable, although there is evidence that the public adopts the language of both parties' elites in a roughly symmetric fashion. Methodologically, the automated analysis of elite rhetoric and open-ended survey questions shows considerable promise in illuminating elite-mass interactions. [Paper (older version)]


02:15 - 03:45:  Jake Bowers

 Dept of Political Science, Univ of Illinois

 "How can machine learning improve precision in experiments? Did the London bombings change social capital in the UK?"

                          [Abstract]The design of a randomized study guarantees not only clear and “interpretable comparisons”(Kinder and Palfrey, 1993, page 7) but valid statistical tests even in the absence of large samples or known data generating processes for outcomes (Fisher, 1935, Chap 2). Yet, while design alone yields valid tests the tests could lack power: a valid but wide confidence interval may be more useful than a misleadingly narrow confidence interval, but still shed little light on the theory motivating the study. After a brief demonstration of Fisher’s statistical framework, we show a method by which a researcher may use substantive background knowledge about outcomes in order to increase the power of her statistical tests. Combining substance and design in this par- ticular way enables valid and powerful tests. We combine modern methods of machine learning with Fisher’s conceptual framework and survey sampling based design-based statistical inference originating with Neyman in order to maximize power without compromising the integrity of the resulting statistical inference. We apply our ideas in the context of a natural experiment created by the London subway bombings of 2005. [Paper (older version)]


04:00 - 05:30:  Jacob Montgomery

 Dept of Political Science, Washington University in St. Louis

 "The efficient measurement of personality: Adaptive personality inventories for survey research."

                          [Abstract]Recent scholarship in political science has expanded our understanding of how personality affects political behaviors, attitudes, and learning. However, a major obstacle to expanding this research agenda is that many established personality inventories contain far too many questions for inclusion on surveys. In response, researchers typically select a subset of items to administer, a practice that can dramatically lower measurement precision and accuracy. In this paper, I outline an alternative method – adaptive personality inventories (APIs) – for including large personality batteries on surveys while minimizing the number of questions each respondent must answer. Building on results in Montgomery and Cutler (2013), I implement a computerized adaptive testing technique for categorical survey items appropriate for the measurement of personality traits. I provide simulation and experimental evidence demonstrating the benefits of the method in terms of measurement accuracy and precision and validate an API included on the 2016 American National Election Study Pilot Study. [Paper]


05:30 - 06:30:  Post Papers Discussion Event


06:45               Dinner for Speakers and Invited Faculty Guests

For more information, please contact Jonathan Nagler

Previous NEMP Editions

  • NEMP 2015
  • NEMP 2014
  • NEMP 2013
  • NEMP 2012
  • NEMP 2011
  • NEMP 2010