2004/05/01 by Nathaniel Beck, Gary King, Langche Zeng · 1 citation
Economics, Econometrics and Finance · Engineering · Social Sciences · #Computer science #Defense, Military, and Policy Studies #Economic Sanctions and International Relations #Economics #Engineering #International Relations and Foreign Policy #Interpretation (philosophy) #Operations research #Political science #Positive economics
paper · doi:10.1017/s0003055404001212
openalex publication_date 2004/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/11
In this article, we show that de Marchi, Gelpi, and Grynaviski's substantive analyses are fully consistent with our prior theoretical conjecture about international conflict. We note that they also agree with our main methodological point that out-of-sample forecasting performance should be a primary standard used to evaluate international conflict studies. However, we demonstrate that all other methodological conclusions drawn by de Marchi, Gelpi, and Gryanaviski are false. For example, by using the same evaluative criterion for both models, it is easy to see that their claim that properly specified logit models outperform neural network models is incorrect. Finally, we show that flexible neural network models are able to identify important empirical relationships between democracy and conflict that the logit model excludes a priori; this should not be surprising since the logit model is merely a limiting special case of the neural network model.