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ID:
176039
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| Summary/Abstract |
Expert-coded datasets provide scholars with otherwise unavailable data on important concepts. However, expert coders vary in their reliability and scale perception, potentially resulting in substantial measurement error. These concerns are acute in expert coding of key concepts for peace research. Here I examine (1) the implications of these concerns for applied statistical analyses, and (2) the degree to which different modeling strategies ameliorate them. Specifically, I simulate expert-coded country-year data with different forms of error and then regress civil conflict onset on these data, using five different modeling strategies. Three of these strategies involve regressing conflict onset on point estimate aggregations of the simulated data: the mean and median over expert codings, and the posterior median from a latent variable model. The remaining two strategies incorporate measurement error from the latent variable model into the regression process by using multiple imputation and a structural equation model. Analyses indicate that expert-coded data are relatively robust: across simulations, almost all modeling strategies yield regression results roughly in line with the assumed true relationship between the expert-coded concept and outcome. However, the introduction of measurement error to expert-coded data generally results in attenuation of the estimated relationship between the concept and conflict onset. The level of attenuation varies across modeling strategies: a structural equation model is the most consistently robust estimation technique, while the median over expert codings and multiple imputation are the least robust.
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| 2 |
ID:
148041
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| Summary/Abstract |
A prominent international-relations theory posits that mutual optimism, due to two sides holding divergent estimates of their relative bargaining power, causes interstate conflict. We develop a theory of mutual optimism in which conflicting bargaining power estimates arise from asymmetric information about which, if any, third parties will join either side in a military dispute. We contend that secret alliances can generate mutual optimism, which increases the probability of conflict. By exploiting secret alliances as a measurable source of private information, we provide the first systematic test of mutual optimism that directly assesses a state's secret capabilities. Optimism exists when a state's secret allies are more numerous or powerful than anticipated by opponents. Our empirical tests—as well as robustness checks—strongly support our theoretical expectation. We conclude that mutual optimism is an empirically, as well as theoretically, important cause of interstate conflict.
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