Borrow it

The Resource Improving Quantitative Studies of International Conflict: A Conjecture

Improving Quantitative Studies of International Conflict: A Conjecture

Resource Information

The item Improving Quantitative Studies of International Conflict: A Conjecture represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Bowdoin College Library.
This item is available to borrow from 1 library branch.

Summary: In this article, the authors address a well-known but infrequently discussed problem in the quantitative study of international conflict: despite immense data collections, prestigious journals, and sophisticated analyses, empirical findings in the literature on international conflict are often unsatisfying. Many statistical results change from article to article and specification to specification. Accurate forecasts are nonexistent. The authors offer a conjecture about one source of this problem: the causes of conflict, theorized to be important but often found to be small or ephemeral in prior research, are indeed tiny for the vast majority of dyads, but they are large, stable, and replicable wherever the ex ante probability of conflict is large. The authors provide a direct test of their conjecture by formulating a statistical model that includes its critical features. The approach, a version of a "neural network" model, uncovers some structural features of international conflict and also functions as an evaluative measure by forecasting. Moreover, it is easy to evaluate whether the neural network model is a statistical improvement over the simpler models commonly used

Work

Label: Improving Quantitative Studies of International Conflict: A Conjecture

Title: Improving Quantitative Studies of International Conflict: A Conjecture

Summary: In this article, the authors address a well-known but infrequently discussed problem in the quantitative study of international conflict: despite immense data collections, prestigious journals, and sophisticated analyses, empirical findings in the literature on international conflict are often unsatisfying. Many statistical results change from article to article and specification to specification. Accurate forecasts are nonexistent. The authors offer a conjecture about one source of this problem: the causes of conflict, theorized to be important but often found to be small or ephemeral in prior research, are indeed tiny for the vast majority of dyads, but they are large, stable, and replicable wherever the ex ante probability of conflict is large. The authors provide a direct test of their conjecture by formulating a statistical model that includes its critical features. The approach, a version of a "neural network" model, uncovers some structural features of international conflict and also functions as an evaluative measure by forecasting. Moreover, it is easy to evaluate whether the neural network model is a statistical improvement over the simpler models commonly used

http://library.link/vocab/creatorName

http://library.link/vocab/relatedWorkOrContributorName

Label: Improving Quantitative Studies of International Conflict: A Conjecture

Label: Improving Quantitative Studies of International Conflict: A Conjecture

Bowdoin College LibraryBorrow it

3000 College Station, Brunswick, ME, 04011-8421, US

43.907093 -69.963997

Structured data from the Bibframe namespace is licensed under the Creative Commons Attribution 4.0 International License by Bowdoin College Library. Additional terms may apply to data associated with third party namespaces.