203
Views
0
CrossRef citations to date
0
Altmetric
Articles

Causal inference in political science research: global trends and implications on Philippine political scholarship

Pages 306-328 | Published online: 18 Dec 2023
 

ABSTRACT

This paper examines the role of causal inference in the on-going methodological debate in political science research. Here, we critically engage the extant literature, take stock of the major debates, articulate key gaps and its limitations. Then, we leverage published journal articles in Web of Science (WoS) database collections and analyze them according to their publication years, topics, research areas, and countries/regions that they focused on. Finally, we did the same review at the country-level to look for nuanced patterns. We found that there is an influx of causal inference articles that are primarily election-related and concerns about the government and law. A good number of these studies focused in developed countries, while only limited interest in developing countries. Ultimately, we demonstrate that while the trend of much political science research has been the pursuit of causal inference, many regional and national-level studies of this kind remain scant and marginal. This is particularly revealing in the Philippine context which suggests potentially minimal exposure and lesser interaction and dissemination of the core ideas of establishing cause-and-effect in social science. This bears implications to the state and trajectory of empirical political works in Philippine political science.

Acknowledgments

This manuscript benefits a great deal from the brilliant comments and insights of Dr. Poe Yu-ze Wan and Prof. Brian C.H. Fong during the Southern Taiwan Social Sciences Research School Conference Program last July 21-22, 2023 at the National Sun Yat-sen University. Part of this paper was developed during the completion of my PhD studies. I would like to especially thank the members of my committee on Political Methodology: Dr. Frank C.S. Liu, Dr. Titus C. Chen, Dr. Rou-len Chen and Dr. Jinh-yeok Jang for their critical and constructive feedback. I am also grateful to my classmates Dr. Ahmet Tulga, Dr. Daniel Davies, Tonny Dian Effendi (PhD Cand) and Ariel Blenkitni (PhD Cand) for the bright conversations we had over this topic. Lastly, I would like to thank the editor and reviewers of the Asian Journal of Political Science for their helpful feedback. All errors however are my own.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 It should be stated that the works of Fiva and Smith (Citation2018) and López-Moctezuma et al. (Citation2022) have appeared in the American Political Science Review—the world's leading journal in political science.

2 Some of them are wrongly categorized or included as causal since this type of research is heavily reliant on search terms. By extension, there might be some related studies that were excluded which may be used in further research.

Additional information

Notes on contributors

Ronald A. Pernia

Ronald A. Pernia is an Assistant Professor in the Political Science Program of the College of Social Sciences of the University of the Philippines Cebu. His research interest includes public opinion and comparative political behavior, autocratization and democratization; political trust and authoritarian values; regression analyses and multilevel modelling educational politics and educational research.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 308.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.