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Title Signaling repression: How citizens assess personal risk
Post date 09/29/2015
C1 Background and Explanation of Rationale In this study I test whether and how citizens interpret past repressive events as signals about their own personal safety. I use conjoint analysis (Hainmueller et al 2014) to present subjects with a randomly assigned scenario about a past repressive event in which five parameters are varied: the temporal proximity to the next election, the identity of the victim, the province (and by association, the urban-rural status and ethnicity), the severity of the violence, and the credibility of the source. Subjects are asked separately about two scenarios, and are then asked to rank which of these scenarios would make them more worried about their own personal safety. Second, I test whether opposition supporters that are poor, female, and have low self-efficacy are more likely to report fear than anger in response to a repressive situation. I find using the pilot data from the conjoint analysis that people who are high in self-efficacy are significantly more likely to report that they would feel anger and less likely to feel fear in response to the described scenarios of repressive violence. Similarly, people high in self-efficacy report that it is more likely that they would go to an opposition rally after the repressive event. This preliminary evidence thus suggests that self-efficacy does drive heterogeneity in the emotional responses to repression. Third, I test whether citizens intepret these signals differently if they are in a state of experimentally-induced fear. The emotion induction treatment is preregistered under the pre-analysis plan submitted on 9/29/2015 under the title The psychology of political risk: Replication and extension.
C2 What are the hypotheses to be tested? H1: Subjects will interpret events that occur closer to elections as signaling higher personal risk. H2A: Subjects will interpret events in which the victim is more similar or familiar as signaling higher personal risk. This hypothesis implies that events against "a voter" or "a voter you know" will signal higher risk than activists or candidates. H2B: Subjects will interpret events in which the victim is a publicly visible figure as costlier for the regime and thus signaling a higher personal risk. If the costliness of the signal is more important than the similarity of the target, then repression of public figures like MP candidates will signal the most risk. H3: Subjects will interpret events against people in their own province as signaling higher personal risk than events in other provinces. H4: Subjects will interpret more severe events (murder > abduction > beating > threatened) as signaling higher personal risk. H5: Subjects will interpret events as signaling higher personal risk if they come from more credible sources (friend > opposition activist > ruling party activist). H6: Subjects will not interpret events differently if they are in a state of experimentally-induced fear. H7: The same characteristics of events that make subjects worried for their own safety will make them angrier. H8A: Women will be more likely to feel fear and less likely to report anger after repressive events. H8B: Women will be less likely to report that they would engage in pro-opposition action after repressive events. H9A: People with lower socioeconomic status will be more likely to feel fear and less likely to report anger after repressive events. H9B: People with lower socioeconomic status will be less likely to report that they would engage in pro-opposition action after repressive events. H10A: People with low self-efficacy will be more likely to feel fear and less likely to report anger after repressive events. H10B: People with low self-efficacy will be less likely to report that they would engage in pro-opposition action after repressive events.
C3 How will these hypotheses be tested? * Hypotheses will be tested using regression analysis. The first specification will only include the treatment variables and the second will include individual-level covariates including gender, age, an assets index, and education. All will include community fixed effects.
C4 Country Zimbabwe
C5 Scale (# of Units) 700
C6 Was a power analysis conducted prior to data collection? No
C7 Has this research received Insitutional Review Board (IRB) or ethics committee approval? Yes
C8 IRB Number IRB-AAAP2200
C9 Date of IRB Approval 9/15/2015
C10 Will the intervention be implemented by the researcher or a third party? Researchers
C11 Did any of the research team receive remuneration from the implementing agency for taking part in this research? not provided by authors
C12 If relevant, is there an advance agreement with the implementation group that all results can be published? not provided by authors
C13 JEL Classification(s) D74, D72, D81, D84