|
Activity Number:
|
164
- Social Statistics Speed Session
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
|
|
Sponsor:
|
Social Statistics Section
|
|
Abstract #318368
|
|
|
Title:
|
On the Causal Effect of Flipping the Party Order of Candidates in North Carolina’s Nonpartisan Elections
|
|
Author(s):
|
Alessandro Arlotto and Alexandre Belloni and Fei Fang* and saša peke?
|
|
Companies:
|
Duke University and Duke University and Duke University and Duke University
|
|
Keywords:
|
Flipping Effect;
Causal Inference;
Clustered Data;
Random Effect Model
|
|
Abstract:
|
This work investigates the impact of ballot design on election outcomes. More specifically, it measures the causal effect of flipping the party order of the candidates running for non-partisan offices. Utilizing data collected from the North Carolina State Board of Elections from 2008 to 2020, our results suggest a heterogeneous and downward flipping effect across vote shares of major partisan contests. In the analysis, we tackle different issues including correlated units clustered by contests and the fact that the treatment assignment mechanism may deviate from cluster randomization due to the uncertainty about which candidates will file for election.
|
Authors who are presenting talks have a * after their name.
