A01=Atin Basuchoudhary
A01=James T. Bang
A01=John David
A01=Tinni Sen
Armed Conflict
Author_Atin Basuchoudhary
Author_James T. Bang
Author_John David
Author_Tinni Sen
Category=GTU
Category=JP
Category=KC
Civil War
Defense Policy
Economics of Conflict
Economics of Defence
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Machine Learning
National Security
Predicting Conflict
Theory of Civil Conflict
Product details
- ISBN 9781498520676
- Weight: 454g
- Dimensions: 159 x 231mm
- Publication Date: 15 Sep 2018
- Publisher: Bloomsbury Publishing Plc
- Publication City/Country: US
- Product Form: Hardback
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This book should be useful to anyone interested in identifying the causes of civil conflict and doing something to end it. It even suggests a pathway for the lay reader. Civil conflict is a persistent source of misery to humankind. Its study, however, lacks a comprehensive theory of its causes. Nevertheless, the question of cooperation or conflict is at the heart of political economy. This book introduces Machine Learning to explore whether there even is a unified theory of conflict, and if there is, whether it is a ‘good’ one. A good theory is one that not only identifies the causes of conflict, but also identifies those causes that predict conflict. Machine learning algorithms use out of sample techniques to choose between competing hypotheses about the sources of conflict according to their predictive accuracy. This theoretically agnostic ‘picking’ has the added benefit of offering some protection against many of the problems noted in the current literature; the tangled causality between conflict and its correlates, the relative rarity of civil conflict at a global level, missing data, and spectacular statistical assumptions. This book argues that the search for a unified theory of conflict must begin among these more predictive sources of civil conflict. In fact, in the book, there is a clear sense that game theoretic rational choice models of bargaining/commitment failure predict conflict better than any other approach. In addition, the algorithms highlight the fact that conflict is path dependent - it tends to continue once started. This is intuitive in many ways but is roundly ignored as a matter of science. It should not. Further, those causes of conflict that best predict conflict can be used as policy levers to end or prevent conflict. This book should therefore be of interest to military and civil leaders engaged in ending civil conflict. Last, though not least, the book highlights how the sources of conflict affect conflict. This additional insight may allow the crafting of policies that match a country’s specific circumstance.
Atin Basuchoudhary, is professor of business and economics at Virginia Military Institute
James T. Bang, is professor of economics at St. Ambrose University
Tinni Sen, is professor of business and economics at Virginia Military Institute
John David, is professor of applied mathematics at Virginia Military Institute
