June 9-12
Instructors: Randall Calvert and Andrew Martin (both of Washington University in St. Louis)

Although most participants in the Summer Institute know the basics of rational choice theory and statistical analysis, it is necessary to cover some basic techniques from a standpoint that will prepare participants for the advanced seminars. Commentators on rational choice theory have asserted that such theories generate only point predictions, unsuitable for testing. The Foundations seminar presents important varieties of rational choice models, specifically spatial voting models and non-cooperative game theory, in a form that emphasizes the techniques by which these models can be used to generate testable implications through comparative statics analysis and the analysis of population variations in the parameter values. A key component of the Foundations seminar is to provide tools with which students can develop their own statistical models to test predictions derived from formal theories. Basic courses in statistical methods oftentimes give scant coverage to the following techniques fundamental to the Summer Institute's advanced seminars: maximum likelihood estimation, Bayesian inference, model specification for comparative statics predictions, model comparison, and simulation. Finally, software to be used in the subsequent advanced seminars is introduced.

• Syllabus
• Ashworth and Bueno de Mesquita, 2006. Monotone Comparative Statics for Models of Politics. (local, JSTOR)
• Cameron and Morton, 2002. Formal Theory Meets Data. (local)
• Casella and George, 1992. Explaining the Gibbs Sampler. (local, JSTOR)
• Chib and Greenberg, 1995. Understanding the Metropolis-Hastings Algorithm. (local, JSTOR)
• Kass and Raftery, 1995. Bayes Factors. (local, JSTOR)
• Krehbiel, 1988. Spatial Models of Legislative Choice. (local, JSTOR)
• Kuhnert and Venables, 2005. An Introduction to R. (CRAN)
• Martin, for the Oxford Handbook of Political Methodology. Bayesian Analysis. (local)
• Raftery, 1995. Bayesian Model Selection in Social Research. (local, JSTOR)
• Simon and Blume, 1994. Mathematics for Economists, chapter 15, "Implicit Functions and Their Derivatives". (local)

• DeGroot and Schervish, 2002. Probability and Statistics. (Amazon)
• Gibbons, 1992. Game Theory for Applied Economists. (Amazon) (optional)
• Greenberg, 2007. Introduction to Bayesian Econometrics. (Amazon) [This book is also recommended for Rob Walker's seminar.]
• Morrow, 1994. Game Theory for Political Scientists. (Amazon) (optional)
• Osborne, 2003. An Introduction to Game Theory. (Amazon)

• Martin notes: day 1, day 2, day 3, day 4, bvn
• Martin sample R code: battleofsexes.R, binomialbeta.R, bvn.R, exponential.R, nonconj.R, regressionml.R
• Martin homework: day 1, day 2, day 3
• Martin movies: Gibbs, Metropolis-Hastings, Mixing
• Calvert notes: day 1, day 2
• Calvert homework: Synergy, Sequential synergy
• Homework solutions: symmetric.R, altruism.R
• Haptonstahl Lab R code: lab 2, (MLE) lab 3 (Bayes)

June 13-14
Instructor: Mark Fey (University of Rochester)

Much of the political science literature suffers from a disconnect between theory and the statistical techniques used to test or analyze theory. During this module, we will examine methods for explicity linking theory and statistical analysis, especially in a strategic context. Topic covered in this section will include random utility models (RUM), selection models, quantal response equilibrium (QRE), and structural econometric models of strategic interaction, including signaling.

• Syllabus
• Anderson, Goeree, and Holt, 2002. The Logit Equilibrium: A Perspective on Intuitive Behavioral Anomalies. (local, JSTOR)
• Bas, Signorino, and Walker, 2008. Statistical Backwards Induction: A Simple Method for Estimating Recursive Strategic Models. (local, Oxford Journals)
• Capra, Goeree, Gomez, and Holt, 1999. Anomalous Behavior in a Traveler's Dilemma?. (local, JSTOR)
• Carson, 2003. Strategic Interaction and Candidate Competition in U.S. House Elections: Empirical Applications of Probit and Strategic Probit Models. (local, Oxford Journals)
• Carson, 2005. Strategy, Selection, and Candidate Competition in U.S. House and Senate Elections. (local, EBSCO)
• Fey, McKelvey, and Palfrey, 1996. An Experimental Study of Constant-sum Centipede Games. (local)
• Gent, 2007. Strange Bedfellows: The Strategic Dynamics of Major Power Military Interventions. (local, Blackwell Synergy)
• Goeree and Holt, 2005. An Explanation of Anomalous Behavior in Models of Political Participation. (local, Cambridge Journals)
• Goeree, Holt, and Palfrey, 2005. Regular Quantal Response Equilibrium. (local, SpringerLink)
• Guarnaschelli, McKelvey, and Palfrey, 2000. An Experimental Study of Jury Decision Rules. (local, JSTOR)
• Haile, Hortacsu, and Kosenok, 2008 (2006 draft). On the Empirical Content of Quantal Response Equilibrium. (local)
• Leblang, 2003. To Devalue or to Defend: The Political Economy of Exchange Rate Policy. (local, Blackwell Synergy)
• Levine and Palfrey, 2007. The Paradox of Voter Participation? A Laboratory Study. (local, Cambridge Journals)
• Lewis and Schultz, 2003. Revealing Preferences: Empirical Estimation of a Crisis Bargaining Game with Incomplete Information. (local, Oxford Journals)
• McKelvey and Palfrey, 1995. Quantal Response Equilibria for Normal Form Games. (local, ScienceDirect)
• McKelvey and Palfrey, 1996. A Statistical Theory of Equilibrium in Games. (local)
• McKelvey and Palfrey, 1998. Quantal Response Equilibria for Extensive Form Games. (local, SpringerLink)
• Signorino, 1999. Strategic Interaction and the Statistical Analysis of International Conflict. (local, JSTOR)
• Signorino, 2003. Structure and Uncertainty in Discrete Choice Models. (local, Oxford Journals)
• Signorino and Yilmaz, 2003. Strategic Misspecification in Regression Models. (local, JSTOR)
• Smith, 1999. Testing Theories of Strategic Choice: The Example of Crisis Escalation. (local, JSTOR)
• Wand, 2006. Comparing Models of Strategic Choice: The Role of Uncertainty and Signaling. (local, Oxford Journals)

• Notes: day 1, day 2
• Data file
• Lab: Examples of estimating an experimental QRE

For over fifty years, the spatial model of voting has informed a great deal of rational choice scholarship on voting and decision making in legislative and judicial institutions throughout the world.  It is no exaggeration to say that a great deal about what is known about voting in parliaments relies on the logic of the spatial model. The literature also suggests that voting in a well-defined issue space (of typically low dimensionality) explains a good deal of voting by the mass public. The spatial model has also spawned a tremendous amount of theoretical development. In general, we know that voting in multi-dimensional issue spaces is inherently unstable (McKelvey 1979, Schofield 1977), unless choice is constrained in some fashion, such as structure induced equilibrium (Shepsle 1979). This course seeks to better connect intense theoretical interest in spatial voting models with data analysis.  How does one take voting data from a legislative body and estimate ideal points? How does one take a battery of issue questions on a survey and summarize the issue space? Given estimates of ideal points in such a space, how does one use them in other models? How does one go about computing equilibrium behavior from spatial models? In this course, cutting-edge methodological tools are taught that will allow students to (a) operationalize the spatial model in their own research; (b) use the spatial model in other statistical models of behavior; and (c) use computational approaches to compute equilibrium predictions of various sorts of formal models.

• Syllabus
• Albert, 1992. Bayesian Estimation of Normal Ogive Item Response Curves Using Gibbs Sampling. (local, JSTOR)
• Bailey, 2001. Ideal Point Estimation with a Small Number of Votes: A Random-Effects Approach. (local, Polmeth)
• Bianco, 2004. The Uncovered Set and the Limits of Legislative Action. (local, Oxford Journals)
• Clinton, 2001. Agenda Constrained Legislator Ideal Points and the Spatial Voting Model. (local, Polmeth)
• Clinton, Jackman, and Rivers, 2004a. "The Most Liberal Senator"? Analyzing and Interpreting Congressional Roll Calls. (local, Cambridge Journals)
• Clinton, Jackman, and Rivers, 2004b. The Statistical Analysis of Roll Call Data. (local, JSTOR)
• Cox and Poole, 2002. On Measuring Partisanship in Roll-Call Voting: The U.S. House of Representatives, 1877-1999. (local, JSTOR)
• Heckman and Snyder, 1997. Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators. (local, JSTOR)
• Jackman, 2000a. Estimation and Inference Are Missing Data Problems: Unifying Social Science Statistics via Bayesian Simulation. (local, Polmeth)
• Jackman, 2000b. Estimation and Inference via Bayesian Simulation: An Introduction to Markov Chain Monte Carlo. (local, JSTOR)
• Jackman, 2001. Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking. (local, Polmeth)
• Jackman, 2004. Bayesian Analysis for Political Research. (local, Annual Reviews)
• Jackman, 2008 (draft -- do not redistribute.) Bayesian Analysis for the Social Sciences. (local Note: 73MB)
• Martin and Quinn, 2002. Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999. (local, Oxford journals)
• McCarty, Poole, and Rosenthal. The Hunt for Party Discipline in Congress. (local, JSTOR)
• Nokken and Poole, 2004. Congressional Party Defection in American History. (local)
• Poole, 2000. Nonparametric Unfolding of Binary Choice Data. (local, Polmeth)
• Snyder and Groseclose, 2000. Estimating Party Influence in Congressional Roll-Call Voting. (local, JSTOR)

• pscl R package
• MCMCpack R package
• WinBUGS

• Poole, 2005. Spatial Models of Parliamentary Voting. (Amazon)
• Poole and Rosenthal, 2000. Congress: A Political-Economic History of Roll Call Voting. (Amazon)

June 19-21, 23
Instructor: Rick Wilson (Rice University) and Catherine Eckel (UT Dallas)

As in other sciences, the development of rigorous, deductive theory leads to hypotheses that demand testing. Laboratory experiments are intended to provide the most controlled tests of these hypotheses. In political science, laboratory experiments play a critical role since so many of the theories presume knowledge of preferences which are typically unknown in the field. Political science experiments typically guarantee subjects differing financial rewards for different outcomes, thereby inducing known preference rankings over those outcomes. Typically, different treatments will be identical except for one key theoretical variable, which may be the institutional voting rule, information conditions, communication possibilities, or preferences. With random assignment of subjects to treatments, differences across treatments may be confidently attributed to the treatment variable.

Topics covered will include voting experiments, public good experiments, tests of non-cooperative bargaining theory, experiments on information, and recent innovations in political science experimentation. We will discuss links between theory and experiment, experimental design, the role of pilot experiments, experimental technique, data gathering and data analysis. Students will have a chance to participate both as subjects and as observers, and will be asked to design an experiment. Readings will be reports of experiments in political science and economics journals.

Professor Rick Wilson of Rice University is the instructor of this course. In addition to historical research on institutions of American politics, Rick has done some of the most innovative and powerful experiments in the discipline. He has designed and administered experiments on strategic voting, agendas and agenda costs, and repeated prisoners' dilemma games, coordination games, and ultimatum games, among others. He has received numerous National Science Foundation grants in support of his experimental research.

• Syllabus
• Andreoni, 1990. Impure Altruism and Donations to Public Goods: A Theory of Warm-Glow Giving. (local, JSTOR)
• Ashley, Ball, and Eckel, 2005 working paper. Motives for Giving: A Reanalysis of Two Classic Public Goods Experiments. (local, UT Dallas)
• Cadsby and Maynes, 1998. Choosing Between a Socially Efficient and Free-Riding Equilibrium: Nurses versus Economics and Business Students. (local, ScienceDirect)
• Eckel and Grossman, 1998. Are Women Less Selfish Than Men? Evidence from Dictator Experiments. (local, JSTOR)
• Eckel and Grossman, 2007 working paper. Encouraging Giving: Subsidies in the Field. (local, Walton)
• Eckel, Johnson, and Wilson, 2002. Fairness and Rejection in the Ultimatum Game. (local, Oxford)
• Forsythe, Nelson, Neumann, and Wright, 1992. Anatomy of an Experimental Political Stock Market. (local, JSTOR)
• Gerber, Green, and Larimaer, 2008. Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment. (local, Cambridge)
• Haney, Herzberg, and Wilson, 1992. Advice and Consent: Unitary Actors, Advisory Models, and Experimental Tests. (local, JSTOR)
• Isaac and Walker, 1988. Group Size Effects in Public Goods Provision: The Voluntary Contributions Mechanism. (local, JSTOR)
• McKelvey and Ordeshook, 1985. Sequential Elections with Limited Information. (local, JSTOR)
• Morton, 1993. Incomplete Information and Ideological Explanations of Platform Divergence. (local, JSTOR)
• Palfrey, 2005 working paper. Laboratory Experiments in Political Economy. (local, CEPS)
• Webster, 2007. Funding Experiments, Writing Proposals. (local)
• Webster and Sell, 2007. Why Do Experiments? (local)
• Whitt and Wilson, 2007. Public Goods in the Field: Katrina Evacuees in Houston. (local, EBSCO)
• Wilson, 2007. Voting and Agenda Setting in Political Science and Economics. (local)
• Wilson and Eckel, 2006. Judging a Book by Its Cover: Beauty and Expectations in the Trust Game. (local, JSTOR)
• Wilson and Herzberg, 1987. Negative Decision Powers and Institutional Equilibrium: Experiments on Blocking Coalitions. (local, JSTOR)
• Wolfers and Zitzewitz. Prediction Markets. (local, JSTOR)

• Webster and Sell, 2007. Laboratory Experiments in the Social Sciences. (Amazon)

June 24-26
Instructor: Keith Krehbiel (Stanford University)

In recent years, theoretical advances concerning legislative institutions, legislative parties, and the individual behavior of legislators have generated many methodological challenges. A central concern of the field is the development of appropriate tests of theories about the choice of formal and informal institutions. Closely related are theories of individual behavior in a strategic context. The seminar is designed to give intensive consideration of several problems at the intersection of theory and method.

The instructor for the seminar is Keith Krehbiel. Professor Krehbiel is the Edward B. Rust Professor of Political Science in the Graduate School of Business at Stanford University. He is the author of Pivotal Politics (1998), Information and Legislative Organization (1991), and numerous articles on the theory and method of legislative politics.  He won the GSB’s Sloan Award for Teaching Excellence in 2000 and the Distinguished Service Award for PhDs in 2007.

• Syllabus
• Basu, 1994. Scientists Studying Possible Link Between Signals, Earthquakes, Continuing Research; Still Just a Theory. (local)
• Chiou and Rothenberg, 2003. When Pivotal Politics Meets Partisan Politics. (local, JSTOR)
• Clinton, 2007. Lawmaking and Roll Calls. (local, Blackwell Synergy)
• Clinton, 2008. Congress, Lawmaking, and Political Failure? The Case of the Fair Labor Standards Act. (local)
• Cox and McCubbins, 2002. Agenda Power in the U.S. House of Representatives, 1877 to 1986. (local)
• Diermeier and Krehbiel, 2003. Institutionalism as Methodology. (local, Sage journals)
• Gorman, 2003. Contrary to Orwell, Democracy Rules on the Big Animal Farm. (local, NY Times)
• Groseclose, 1996. An Examination of the Market for Favors and Votes in Congress. (local, Blackwell Synergy)
• An exchange in Political Analysis, 2003
  • Krehbiel: The Coefficient of Party Influence. (local, Political Analysis)
  • Groseclose and Snyder: Interpreting the Coefficient of Party Influence: Comment on Krehbiel. (local, Political Analysis)
  • Krehbiel: Asymmetry in Party Influence: Reply. (local, Political Analysis)
• Hirsch, 2007. Voting Error and Econometric Testing of Complete Information Theories of Lawmaking. (local)
• Kramer, 1986. Political Science as Science. (local)
• Krehbiel, 1993. Where's the Party? (local, JSTOR)
• Krehbiel, 2000. Party Discipline and Measures of Partisanship. (local, JSTOR)
• Krehbiel, Meirowitz, and Woon, 2005. Testing Theories of Lawmaking. (local)
• Krehbiel, 2006 (2005 copy). Pivots. (local)
• Krehbiel, 2007. Partisan Roll Rates in a Nonpartisan Legislature. (local, Oxford journals)
• McCarty, Poole, and Rosenthal, 2001. The Hunt for Party Discipline in Congress. (local, JSTOR)
• Primo, Binder, and Maltzman, 2008. Who Consents? A Theoretical and Empirical Examination of Pivotal Senators in Judicial Selection. (local)
• Riker, 1977. The Future of a Science of Politics. (local)
• Schwadron, 1999. For the Musical Alchemist, a New Tack: Cryogenics. (local, NY Times)
• Snyder and Groseclose, 2000. Estimating Party Influence in Congressional Roll-Call Voting. (local, JSTOR)

• Krehbiel, 1998. Pivotal Politics: A Theory of U.S. Lawmaking. (Amazon)

• Components of Institutional Analysis (CIA) framework
• Exercise 1: Is it Science?
• Exercise 2: Vote Buying and Pivots
• Exercise 3: Dynamics of the Cartel Agenda model

June 24-26
Instructor: Robert W. Walker (Washington University in St. Louis)

Formal models have become more common in the political economy of international relations, but a notable disconnect remains between the theoretical and empirical worlds. In this seminar, we will discuss the unique challenges posed by data that are observed across both space and time through the lens of political economy models in international trade, finance, and conflict. We will construct, examine, and/or replicate dynamic models and models of transitions, measurement models, multiple imputation and other advanced techniques in cutting-edge applications of cross-national research using R.

Professor Robert Walker is an Assistant Professor in the Department of Political Science and the Center for Applied Statistics at Washington University in St. Louis specializing in international relations, international political economy, and political methodology.  He is a 2005 Ph. D. in political science (studying under Randy Stone and Curt Signorino) from the University of Rochester and came to Washington University after stints in the Department of Political Science at Texas A & M University, the Department of Government at Dartmouth College and the Institute for Quantitative Social Science at Harvard University.  He teaches courses in international relations and political methodology in the Department of Political Science and courses in applied statistics and econometrics for the Center for Applied Statistics.

• Syllabus
• Bennett and Nordstrom, 2000. Foreign Policy Substitutability and Internal Economic Problems in Enduring Rivalries. (local, JSTOR)
• Clark and Reed, 2005. The Strategic Sources of Foreign Policy Substitution. (local, JSTOR)
• Epstein, Bates, Goldstone, Kristensen, and O'Halloran. Democratic Transitions. (local, JSTOR)
• Greene, 2003. Chapter 15: Simultaneous-Equations Models. (local)
• Lindsey, 2004. Chapter 5: Discrete-time Markov chains. (local)
• Park, 2007. Modeling Structural Changes using Bayesian Inference: Changepoint Analysis of Domestic Determinants of U.S. Presidents' Use of Force Abroad. (local)
• Spirling, 2007. Bayesian Approaches for Limited Dependent Variable Change Point Problems. (local, Oxford journals)
• Stratmann, 1992. The Effects of Logrolling on Congressional Voting. (local, JSTOR)
• Walker, 2003. Statistical Models for Policy Substitutes. (local)
• Walker, 2008 working paper. Credibility, Distributive Theory, and International Financial Policy: Exploring Models of Partisan Substitution in the OECD. (local)
• Walker, 2008 working paper. Democracy and Human Rights to Personal Integrity: History Matters. (local)
• Walker, 2008 working paper. Path, Phat, and State Dependence in Observation-driven Markov Models. (local)

• Greenberg, 2007. Introduction to Bayesian Econometrics. (Amazon) [This book is also recommended for the Foundations seminar.]

• Notes: day 1, day 2