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How Do Observers Assess Resolve?

Published online by Cambridge University Press:  13 June 2019

Joshua D Kertzer*
Affiliation:
Department of Government, Harvard University
Jonathan Renshon
Affiliation:
Department of Political Science, University of Wisconsin-Madison
Keren Yarhi-Milo
Affiliation:
Department of Politics, Princeton University
*
*Corresponding author. Email: jkertzer@gov.harvard.edu
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Abstract

Despite a plethora of theoretical frameworks, IR scholars have struggled with the question of how observers assess resolve. We make two important contributions in this direction. Conceptually, we develop an integrative framework that unites otherwise disconnected theories, viewing them as a set of heuristics actors use to simplify information-rich environments. Methodologically, we employ a conjoint experiment that provides empirical traction impossible to obtain using alternative research designs. We find that ordinary citizens are ‘intuitive deterrence theorists’ who focus to a great extent on capabilities, stakes, signals and past actions in judging resolve. We also find that observers see democracies as less resolved than autocracies (not more), casting doubt on key propositions of democratic credibility theory. Finally, a conceptual replication shows that a group of elite decision makers converge with the US public in how they interpret costly signals, and in viewing democracies as less resolved than autocracies.

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Article
Copyright
Copyright © Cambridge University Press 2019
Figure 0

Table 1 Hypotheses

Figure 1

Figure 1 What indicators do we use to assess resolve?

Figure 2

Table 2 Conjoint study treatments

Figure 3

Table 3 Sample conjoint choice

Figure 4

Figure 2 Predicting perceptions of resolve Note: the figure depicts Average Marginal Component Effects (AMCEs) with 95% clustered bootstrapped confidence intervals. All estimates should be interpreted relative to the baseline category, indicated by the point without horizontal bars at x=0. Thus, for example, states with high capabilities are perceived as 16% more likely to stand firm than states with low capabilities.

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Figure 3 Testing theories of reputation Note: the figures depict AMCEs with 95 per cent clustered bootstrapped confidence intervals. The results in Panel A offer limited support for the Current Calculus hypothesis: actors do draw inferences about resolve based on whether an actor stood firm or backed down in the past, but its effects can be overcome. For instance, if an actor backed down in the past dispute but its capabilities and stakes are both high, observers will still perceive it as being significantly more resolved than an actor that stood firm in the past dispute and has high capabilities but low stakes. The results in Panel B fail to offer support for the attribution theory hypothesis: allies who stand firm indeed gain reputations for resolve, while adversaries who back down gain reputations for irresolution.

Figure 6

Figure 4 Testing democratic credibility theory Note: the figure depicts AMCEs with 95 per cent clustered bootstrapped confidence intervals. The results fail to offer support for the Democratic Credibility hypothesis: although public threats increase the perceived resolve of both democracies and dictatorships relative to when actors do not issue threats, democracies do not get a bigger credibility boost from public threats than dictatorships do.

Figure 7

Figure 5 Comparing our US mass public results with those from foreign decision makers Note: the figure compares the bootstrapped average treatment effects for three factors from the conjoint experiment, in dark grey (calculated using B=2,500 clustered bootstraps), with the bootstrapped average treatment effects for the same three factors in a pair of survey experiments fielded on an elite sample of members of the Israeli Knesset, in light grey (calculated using B=2,500 bootstraps). We find strikingly similar findings across the studies; mobilization is the only factor for which the effect estimates significantly differ. Although the elite distributions are fatter as a result of the much smaller sample size, supplementary analysis in Appendix 5 shows that when we downsample the public results to render the sample sizes more comparable between the two studies, the shape of the pairs of distributions becomes much more similar.

Supplementary material: PDF

Kertzer et al. supplementary material

Appendix

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Kertzer et al. Dataset

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