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Political Orientation and Policy Compliance: Evidence from COVID-19 Mobility Patterns in Korea

  • Sungjin Kim and Hee-Seung Yang EMAIL logo
Published/Copyright: June 2, 2025
The B.E. Journal of Economic Analysis & Policy
From the journal The B.E. Journal of Economic Analysis & Policy Volume 25 Issue 3

Abstract

This study investigates the significant factor influencing widespread non-compliance with COVID-19 preventive measures in Seoul, Korea, through the analysis of spatial mobility data: the disparity between government communications and health policies, alongside the role of political orientation. The study reveals that political messages regarding quarantine success downplayed the severity of the virus, consequently hindering policy compliance during the major waves of COVID-19 in 2020–2021. Individuals with high institutional trust align their mobility behavior with the government’s messaging, increasing social activities. Additional channels come from the area’s occupation and industry characteristics, particularly in sectors with limited remote work availability.

Keywords: political orientation; political message; mobility; social distancing; policy compliance; COVID-19
JEL Classification: I18; O18; J08; R11; D72
Corresponding author: Hee-Seung Yang, School of Economics, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea, E-mail: 

Funding source: Yonsei Signature Research Cluster Program

Award Identifier / Grant number: 2021-22-0011

Acknowledgments

We are grateful to Hyunjin Kwon, Myungkyu Shim, Heather Royer, Xiu Lim, Valerie Ramey, and the seminar participants at Yonsei University, Sogang University, Ewha Womans University, Korea Labor Institute, 2022 Korea Empirical Applied Microeconomics Conference, and the 2023 Korea Economic Association Conference for their helpful comments. This project would not have been possible without the financial support from Yonsei Signature Research Cluster Program (grant number 2021–22–0011). There are no known conflicts of interest associated with this publication that could have influenced its outcome.

Appendix
Appendix Table 1:

Effect on reduction in public transit mobility (binary approval ratings specification).

Variables (1) (2) (3)
Second wave (Aug. 2020 – Sept. 2020) Third wave (Nov. 2020 – Jan. 2021) Fourth wave (Jul. 2021 – Aug. 2021)
Panel A: Presidential election results (May 2017)
High approval rating × Post 1.562*** (0.429) 1.244*** (0.401) 0.774*** (0.258)
High approval rating dummy −0.304 (0.564) −0.180 (0.555) 0.105 (0.707)
Post −23.95*** (0.446) −27.33*** (0.342) −15.32*** (0.340)
Mean of dep. variable −30.53 −36.91 −30.53
Observations 6,784 6,784 6,784
R-squared 0.831 0.886 0.484
Panel B: Legislative election results (April 2020)
High approval rating × Post 1.310*** (0.433) 1.149*** (0.400) 0.906*** (0.257)
High approval rating dummy 0.675 (0.497) 0.994** (0.504) 0.273 (0.635)
Post −23.80*** (0.451) −27.25*** (0.344) −15.36*** (0.341)
Mean of dep. variable −30.50 −36.87 −30.48
Observations 6,768 6,768 6,768
R-squared 0.834 0.889 0.486

  1. Notes: Appendix Table 1 shows the estimation results using an alternative specification with a binary treatment variable D is , deviating from the continuous difference-in-differences setting. The treatment variable is a binary indicator separating wards into high-approval and low-approval groups based on the median percentage of votes received by the president and the ruling party. The dependent variable is the public transit mobility reduction rate for each corresponding period. The variable Post is the post-reference period dummy distinguishing the periods before and after the enforcement of mobility restriction measures. Panels A and B report the results estimated using two separate election outcomes. Each row represents the waves of COVID-19 outbreaks during 2020–2021. Standard errors are clustered at the ward level and reported in parentheses. The level of regional fixed effect is determined by 25 districts. *** p < 0.01, ** p < 0.05, and * p < 0.1.

Appendix Figure 1: Public transit mobility reduction trend by votes received (only Sundays). Notes: Appendix Figure 1 presents mobility reduction rates for wards that have cast large votes on the president or the ruling congress party (blue line) and wards with fewer votes (bold red line). This figure reports the public transit mobility patterns of Sundays only, mitigating the concern that public transit usage on Saturdays may include commuting of workers. The green vertical line separates the treatment and reference periods. Both specifications using the presidential and legislative election results are presented. Among the four major waves of COVID-19, results for the second to fourth waves are provided. Note that the first wave is excluded from the analysis since the disease outbreak had a lesser effect on our region of interest.
Appendix Figure 1:

Public transit mobility reduction trend by votes received (only Sundays). Notes: Appendix Figure 1 presents mobility reduction rates for wards that have cast large votes on the president or the ruling congress party (blue line) and wards with fewer votes (bold red line). This figure reports the public transit mobility patterns of Sundays only, mitigating the concern that public transit usage on Saturdays may include commuting of workers. The green vertical line separates the treatment and reference periods. Both specifications using the presidential and legislative election results are presented. Among the four major waves of COVID-19, results for the second to fourth waves are provided. Note that the first wave is excluded from the analysis since the disease outbreak had a lesser effect on our region of interest.

Appendix Figure 2: False specification test (all months and weeks excluding the main specification periods). Notes: Appendix Figure 2 displays the falsification test results. The figure plots coefficient estimates for every weekend day (Saturday and Sunday) that falls outside the main analysis window, capturing how mobility reduction rates vary by political orientation during periods unaffected by the policy shocks. We divide the timeline into four falsification periods situated before and after the three COVID-19 waves, where throughout these windows no official public messages were issued that might influence mobility. The left column presents results based on the presidential election, while the right column uses results from legislative elections as measures of political orientation. Vertical bars represent the 95 percent confidence intervals. Robust standard errors are clustered at the ward level. Regional fixed effects are determined by 25 districts.
Appendix Figure 2:

False specification test (all months and weeks excluding the main specification periods). Notes: Appendix Figure 2 displays the falsification test results. The figure plots coefficient estimates for every weekend day (Saturday and Sunday) that falls outside the main analysis window, capturing how mobility reduction rates vary by political orientation during periods unaffected by the policy shocks. We divide the timeline into four falsification periods situated before and after the three COVID-19 waves, where throughout these windows no official public messages were issued that might influence mobility. The left column presents results based on the presidential election, while the right column uses results from legislative elections as measures of political orientation. Vertical bars represent the 95 percent confidence intervals. Robust standard errors are clustered at the ward level. Regional fixed effects are determined by 25 districts.

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Received: 2024-03-06
Accepted: 2025-05-09
Published Online: 2025-06-02

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Fair Choices During COVID-19: Firms’ Altruism and Inequality Aversion in Managing a Large Short-Time Work Scheme
  4. Inequality in Health Status During the COVID-19 in the UK: Does the Impact of the Second Lockdown Policy Matter?
  5. The Political Timing of Tax Policy: Evidence from U.S. States
  6. Is it a Matter of Skills? High School Choices and the Gender Gap in STEM
  7. Patent Licensing and Litigation
  8. Class Size, Student Disruption, and Academic Achievement
  9. Political Orientation and Policy Compliance: Evidence from COVID-19 Mobility Patterns in Korea
  10. Social Efficiency of Free Entry in a Vertically Related Industry with Cost and Technology Asymmetry
  11. Carbon Tax with Individuals’ Heterogeneous Environmental Concerns
  12. Equitable Redistribution and Inefficiency under Credit Rationing
  13. Letters
  14. Psychological Well-Being of Only Children: Evidence from the One-Child Policy
  15. Peer Effects in Child Work Decisions: Evidence from PROGRESA Cash Transfer Program
  16. Right Time to Focus? Time of Day and Cognitive Performance
  17. Employee Dissatisfaction and Intentions to Quit: New Evidence and Policy Recommendations
  18. On the Stability of Common Ownership Arrangements
https://doi.org/10.1515/bejeap-2024-0079
Keywords for this article
political orientation; political message; mobility; social distancing; policy compliance; COVID-19

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Fair Choices During COVID-19: Firms’ Altruism and Inequality Aversion in Managing a Large Short-Time Work Scheme
  4. Inequality in Health Status During the COVID-19 in the UK: Does the Impact of the Second Lockdown Policy Matter?
  5. The Political Timing of Tax Policy: Evidence from U.S. States
  6. Is it a Matter of Skills? High School Choices and the Gender Gap in STEM
  7. Patent Licensing and Litigation
  8. Class Size, Student Disruption, and Academic Achievement
  9. Political Orientation and Policy Compliance: Evidence from COVID-19 Mobility Patterns in Korea
  10. Social Efficiency of Free Entry in a Vertically Related Industry with Cost and Technology Asymmetry
  11. Carbon Tax with Individuals’ Heterogeneous Environmental Concerns
  12. Equitable Redistribution and Inefficiency under Credit Rationing
  13. Letters
  14. Psychological Well-Being of Only Children: Evidence from the One-Child Policy
  15. Peer Effects in Child Work Decisions: Evidence from PROGRESA Cash Transfer Program
  16. Right Time to Focus? Time of Day and Cognitive Performance
  17. Employee Dissatisfaction and Intentions to Quit: New Evidence and Policy Recommendations
  18. On the Stability of Common Ownership Arrangements
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