Michael D. Ward

Michael D. Ward

Michael D. Ward is an emeritus professor of Political Science at Duke University, having previously taught at Northwestern University, the University of Colorado, the University of Mendès-France France, and the University of Washington. He is also the founder and president of Predictive Heuristics, a risk analysis firm. He received an A.B (Honors) from Indiana University and a Ph.D. from Northwestern University. He is the recipient of over two dozen research grants and contracts, spanning a variety of topics related to international peace and commerce in the context of the dependencies among international political and economic actors. He also collaborates with political scientists, economists, network scientists, geographers, ethnographers, and remote sensing specialists to study the dynamics of conflict. He is an elected fellow of the Political Methodology Society. Ward has published a dozen books and more than ten dozen refereed articles in a variety of disciplines and languages.

Kristian Gleditsch

Kristian Gleditsch

My research interests include conflict and cooperation, democratization, and spatial dimensions of social and political processes. I am the author of All International Politics is Local: The Diffusion of Conflict, Integration, and Democratization (University of Michigan Press, 2002), Spatial Regression Models (Sage, 2018, with Michael D. Ward), Inequality, Grievances, and Civil War (Cambridge University Press, 2013, with Lars-Erik Cederman and Halvard Buhaug), and journal articles in the American Journal of Political Science, American Political Science Review, Annals of the Association of American Geographers, Biological Reviews, Comparative Political Studies, Conflict and Cooperation, Defence and Peace Economics, Economic History Review, European Journal of International Relations, International Interactions, International Organization, Internasjonal Politikk, International Studies Quarterly, Journal of Conflict Resolution, Journal of Peace Research, Journal of Politics, PLOS One, Political Analysis, Political Psychology, R Journal, and World Politics.

Please also see this related work: Maximum Likelihood Methods