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The effects of state coercion on voting outcome in protest movements: a causal forest approach

Published online by Cambridge University Press:  06 December 2021

Weiwen Yin Open the ORCID record for Weiwen Yin [Opens in a new window] ,
Weidong Huo  and
Danyang Lin
Weiwen Yin
Affiliation:
Department of Asian and Policy Studies, The Education University of Hong Kong, Hong Kong SAR, China
Weidong Huo
Affiliation:
Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, China
Danyang Lin*
Affiliation:
Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, China
*
*Corresponding author. Email: lindy23@mail.sysu.edu.cn
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Abstract

In this research note, we examine how Hong Kong voters respond to police violence in the recent social movement. We use causal forests, a machine learning algorithm, to estimate the impact of tear gas usage specific to each constituency. Based on the 2019 District Council Election outcome, we find that there is heterogeneity in the effect of state coercion on the vote share of pro-democracy candidates, depending on many socioeconomic characteristics of the constituency. The results imply that economic concerns still matter in the struggle to obtain democracy: citizens who sense economic insecurity in social unrest show less disapproval of state violence.

Keywords

Asian politicscomputational modelselections and campaignsvoting behavior
Type
Research Note
Information
Political Science Research and Methods , Volume 11 , Issue 3 , July 2023 , pp. 645 - 653
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the European Political Science Association

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https://doi.org/10.7910/DVN/CX1OGZ
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