The view of institutions as coercion rather than as contracts dominates the comparative politics literature on both institutional creation and the politics of economic reform. The emergence of a collectively optimal tax code in Russia demonstrates the limitations of this emphasis on coercion. This new tax code was not imposed by a strong central leader, mandated by international institutions, or the result of state capture by powerful economic interest groups. Rather, it is the product of a mutually beneficial exchange between the Russian government and the Russian oil companies. Russia's ability to negotiate an effective tax regime also suggests the conditions under which and the microcausal mechanism whereby exogenous shocks promote institutional change and economic reform. Owing to their mutual vulnerability and interdependence, the August 1998 financial crisis generated widely shared perceptions among these actors that the payoffs of cooperation had changed. Yet the economic reform institution that resulted required a series of incremental strategic moves that established common knowledge.

We develop a Bayesian procedure for estimation and inference for spatial models of roll call voting. This approach is extremely flexible, applicable to any legislative setting, irrespective of size, the extremism of the legislators' voting histories, or the number of roll calls available for analysis. The model is easily extended to let other sources of information inform the analysis of roll call data, such as the number and nature of the underlying dimensions, the presence of party whipping, the determinants of legislator preferences, and the evolution of the legislative agenda; this is especially helpful since generally it is inappropriate to use estimates of extant methods (usually generated under assumptions of sincere voting) to test models embodying alternate assumptions (e.g., log-rolling, party discipline). A Bayesian approach also provides a coherent framework for estimation and inference with roll call data that eludes extant methods; moreover, via Bayesian simulation methods, it is straightforward to generate uncertainty assessments or hypothesis tests concerning any auxiliary quantity of interest or to formally compare models. In a series of examples we show how our method is easily extended to accommodate theoretically interesting models of legislative behavior. Our goal is to provide a statistical framework for combining the measurement of legislative preferences with tests of models of legislative behavior.

Theorists argue that deliberation promotes enlightenment and consensus, but scholars do not know how deliberation affects policy opinions. Using the deliberative democracy and public opinion literatures as a guide, I develop a theory of opinion updating where citizens who deliberate revise their prior beliefs, particularly when they encounter consensual messages. A key aspect of this model is that opinion strength moderates the deliberative opinion change process. In two separate propensity score analyses using panel survey data from a deliberative forum and cross-sectional surveys, I show how deliberation and discussion both affect opinions toward Social Security reform. However, deliberation differs from ordinary discussion in that participants soften strongly held views, encounter different perspectives, and learn readily. Thus, deliberation increases knowledge and alters opinions, but it does so selectively based on the quality and diversity of the messages as well as the willingness of participants to keep an open mind.

Beck, King, and Zeng (2000) offer both a sweeping critique of the quantitative security studies field and a bold new direction for future research. Despite important strengths in their work, we take issue with three aspects of their research: (1) the substance of the logit model they compare to their neural network, (2) the standards they use for assessing forecasts, and (3) the theoretical and model-building implications of the nonparametric approach represented by neural networks. We replicate and extend their analysis by estimating a more complete logit model and comparing it both to a neural network and to a linear discriminant analysis. Our work reveals that neural networks do not perform substantially better than either the logit or the linear discriminant estimators. Given this result, we argue that more traditional approaches should be relied upon due to their enhanced ability to test hypotheses.

This article explains how the institutional context of international negotiations influences their outcomes. I argue that issue linkage counteracts domestic obstacles to liberalization by broadening the negotiation stakes. Institutions bolster the credibility of the linkage to make it more effective. I test the argument in the agricultural sector, which has been among the most difficult sectors for governments to liberalize. Statistical analysis of U.S. negotiations with Japan and the EU from 1970 to 1999 indicates that an institutionalized linkage between agricultural and industrial issues encourages agricultural liberalization in both Japan and Europe. Through case studies of key negotiations, I first examine why countries choose to link issues, then show how the linkage changes interest group mobilization and shifts the policy process to promote liberalization.

How do legislators build the reputations they use in bids for reelection? Do they use their personal reputations or associate with other legislators? And how do parties, coalitions, and institutions affect these decisions? Research on how electoral systems affect parties in legislatures frequently focuses on the extent to which electoral rules make legislators more or less ideologically convergent with respect to other members of the chamber—copartisan and not. However, finding equilibrium strategies is often possible only under restrictive institutional and spatial assumptions. Instead of viewing ideology spatially, we conceive of ideological reputations as currencies, used to purchase electoral support in transactions we liken to auctions. In our test of the model, we use bill cosponsorship patterns as an indicator of the reputations incumbents use to purchase electoral support. We show that under relatively common institutional conditions, legislators may have strong incentives to cultivate reputations they must share with their toughest electoral competitors.

The peer review process relies on the professionalism and generosity of those who contribute their time to read and evaluate the work of others. The Editor thanks the following scholars, who served as manuscript reviewers between August 16, 2003 and August 15, 2004.

In this article, we show that de Marchi, Gelpi, and Grynaviski's substantive analyses are fully consistent with our prior theoretical conjecture about international conflict. We note that they also agree with our main methodological point that out-of-sample forecasting performance should be a primary standard used to evaluate international conflict studies. However, we demonstrate that all other methodological conclusions drawn by de Marchi, Gelpi, and Gryanaviski are false. For example, by using the same evaluative criterion for both models, it is easy to see that their claim that properly specified logit models outperform neural network models is incorrect. Finally, we show that flexible neural network models are able to identify important empirical relationships between democracy and conflict that the logit model excludes a priori; this should not be surprising since the logit model is merely a limiting special case of the neural network model.

One of the most important developments over the past three decades has been the spread of liberal economic ideas and policies throughout the world. These policies have affected the lives of millions of people, yet our most sophisticated political economy models do not adequately capture influences on these policy choices. Evidence suggests that the adoption of liberal economic practices is highly clustered both temporally and spatially. We hypothesize that this clustering might be due to processes of policy diffusion. We think of diffusion as resulting from one of two broad sets of forces: one in which mounting adoptions of a policy alter the benefits of adopting for others and another in which adoptions provide policy relevant information about the benefits of adopting. We develop arguments within these broad classes of mechanisms, construct appropriate measures of the relevant concepts, and test their effects on liberalization and restriction of the current account, the capital account, and the exchange rate regime. Our findings suggest that domestic models of foreign economic policy making are insufficient. The evidence shows that policy transitions are influenced by international economic competition as well as the policies of a country's sociocultural peers. We interpret the latter influence as a form of channeled learning reflecting governments' search for appropriate models for economic policy.

Allen, Nicholas, see Orbell, John 1

We address two long-standing survey research problems: measuring complicated concepts, such as political freedom and efficacy, that researchers define best with reference to examples; and what to do when respondents interpret identical questions in different ways. Scholars have long addressed these problems with approaches to reduce incomparability, such as writing more concrete questions—with uneven success. Our alternative is to measure directly response category incomparability and to correct for it. We measure incomparability via respondents' assessments, on the same scale as the self-assessments to be corrected, of hypothetical individuals described in short vignettes. Because the actual (but not necessarily reported) levels of the vignettes are invariant over respondents, variability in vignette answers reveals incomparability. Our corrections require either simple recodes or a statistical model designed to save survey administration costs. With analysis, simulations, and cross-national surveys, we show how response incomparability can drastically mislead survey researchers and how our approach can alleviate this problem.