Abstract.  Democratic political institutions are generally designed to channel public opinion; yet citizens often take to the streets in protest. Why would citizens, provided with formal mechanisms to affect the policy process, resort to extraordinary means? This article argues that the strength of representative institutions influences the likelihood of protest. The democratic institution literature does not address the issue of protest and in the protest literature effects of the democratic governmental structure have been largely underestimated. However, the diversity in government formats across democratic states and the corresponding variation in amount of protests leads one to question the relationship between them. This article identifies the variation in the scale of protests among democratic regimes in Western European countries using the European Protest and Coercion Data and explains protest using variation in the forms of government. Protesters in democratic countries with a weak legislature find it difficult to deliver their demands to government due to the institutional environment. Therefore, they are more inclined to protest than citizens in countries with a strong legislature. This argument is tested along with other structural variables and supported by results from testing models using ordinary least squares with panel‐corrected standard errors.

Data matter. Protest data are no exception. Not all datasets are equal, nor do all have equal validity and reliability. Thus far, there has been no serious debate regarding the quality of protest datasets. Increasing attention to protest studies suggests that now is the time to talk about the sine qua non for growing knowledge in this sub-field of comparative politics. In this paper I emphasize the importance of the underlying data sources. In particular, I argue that protest datasets should be drawn from many sources, particularly as many local sources as possible, in order to provide accurate and meaningful data. To support this contention, I first discuss traditional protest datasets and their limitations and provide suggestions about how to overcome these limitations. Second, I explain an alternative type of dataset coding and its characteristics. And finally, I use statistical tests to illustrate the importance of local sources.I give my sincere and deep thanks to Erik S. Herron and Ronald A. Francisco for reviewing drafts of this paper and giving me indispensable comments and continuous encouragements. I would also like to thank Elizabeth Collins and Omur Yilmaz who edited drafts of this manuscript. My appreciation also goes to anonymous reviews of this paper and the editors of PS: Political Science and Politics. I would like to thank my late farther, Ki-Dae whose love and support were simply endless. I'll share any compliment with them, but only I will take responsibility for any error.

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Korean democratization began in 1988, but by the early 1990s had failed to bring tranquility to the streets or to replace protest with institutionalized political participation. Using data taken from daily Korean sources for 1990 and 1991, I analyze the intimate interaction between coercion and protest. I apply the Lotka-Volterra predator-prey model to test competing hypotheses explaining the interaction. Regarding national protests in general, the results demonstrate that protests and coercion are closely and dynamically related. Unexpectedly, results show that, overall, protests do not necessarily decrease with coercion but do when no coercion at all is applied. My analysis also uncovers variation in the dynamics of state coercion and protest according to types of dissident groups. Of the groups assessed, workers were particularly active in protest. Farmers were the least active, and the Korean regime responded with the least repressive approach toward them. These findings emphasize the importance of daily subnational data. They also show how dynamic analytical models can improve our understanding of the protest-repression relationship.