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Previous statistical studies of the effects of UN peacekeeping have generally suggested that UN interventions have a positive effect on building a sustainable peace after civil war. Recent methodological developments have questioned this result because the cases in which the United Nations intervened were quite different from those in which they did not. Therefore the estimated causal effect may be due to the assumptions of the model that the researchers chose rather than to peacekeeping itself. The root of the problem is that UN missions are not randomly assigned. We argue that standard approaches for dealing with this problem (Heckman regression and instrumental variables) are invalid and impracticable in the context of UN peacekeeping and would lead to estimates of the effects of UN operations that are largely a result of the assumptions of the statistical model rather than the data. We correct for the effects of nonrandom assignment with matching techniques on a sample of UN interventions in post-Cold-War conflicts and find that UN interventions are indeed effective in the sample of post-civil-conflict interventions, but that UN interventions while civil wars are still ongoing have no causal effect.

Chapters of a draft manuscript for a book under contract to the Princeton Studies in Complexity series of Princeton University PressChapter 5 presents findings on satisficing with imperfect information.The introductory chapter sets these findings in context.Any and all comments are profoundly welcome. This is a work in progress: please do not cite without the authors' permission.Versions of this work have been presented at seminars at: Trinity College, Dublin; European University Institute, Fiesole; London School of Economics; University of Bologna; New York University; Columbia University; University of Michigan; Emory University; MIT; Yale University; Duke University; Florida State University; and at the following conferences: Thanks are due for helpful comments from discussants and participants at all of these venues. CONTENTSIntroduction (c5000 words)1. Spatial dynamics of political competition (c4000 words).2. A baseline ABM of multidimensional, multiparty competition (c9000 words) 3. Methods and benchmarking (c18000 words) 4. Endogenous parties; interaction of diverse decision rules (c11000 words) Features of party decision rules (c11250 words)6. Evolutionary dynamics of decision rule selection (c8500 words) 7. Non-policy factors in party competition (c8500 words) 8. Party leaders with policy preferences (c8000 words) 9. Calibrating and testing dynamic models of party competition (c11000 words) Conclusion (c5000 words)References (c1500 words) Electronic Appendices: Supplementary materials on computational results and the full set of computer programs needed to replicate these, one program for each modeling chapter (Ch 2-8), for use and modification by readers Introduction A large part of politics in democratic societies is about the politics of representation. This has to do with how the needs and desires of ordinary citizens play a part in national decision-making, via the public representatives they choose in free and fair elections. A large part of representative politics is about party competition. This has to do with how a small number of organized political parties offer a distinctive and somewhat coherent set of options to voters, who then choose between alternative teams of public representatives. This is why understanding party competition is a core concern of people, be they professional political scientists or interested civilians, who care about politics in democratic societies.This book is about party competition. More specifically, it is about multi-party competition, by which we mean competition for voters' support between more than two parties, opening up the possibility that no one party wins a majority of votes cast. Multiparty competition is much more common than is sometimes supposed. In the European Parliament elections of June 2009, for example, 25 different political parties competed for the support of voters in the United Kingdom -a country sometimes casually thought of as having a two or two-and-a-half party system. Eleven of these parties secured the election of at least one publi...

Party competition for votes in free and fair elections involves complex interactions by multiple actors in political landscapes that are continuously evolving, yet classical theoretical approaches to the subject leave many important questions unanswered. This book offers the first comprehensive treatment of party competition using the computational techniques of agent-based modeling. This exciting new technology enables researchers to model competition between several different political parties for the support of voters with widely varying preferences on many different issues. The book models party competition as a true dynamic process in which political parties rise and fall, a process where different politicians attack the same political problem in very different ways, and where today's political actors, lacking perfect information about the potential consequences of their choices, must constantly adapt their behavior to yesterday's political outcomes. This book shows how agent-based modeling can be used to accurately reflect how political systems really work. It demonstrates that politicians who are satisfied with relatively modest vote shares often do better at winning votes than rivals who search ceaselessly for higher shares of the vote. It reveals that politicians who pay close attention to their personal preferences when setting party policy often have more success than opponents who focus solely on the preferences of voters, that some politicians have idiosyncratic “valence” advantages that enhance their electability—and much more.