Recent scholarship has identified problems in the measurement of party system instability. To limit the conflation of different sources of instability in party systems (e.g., electoral shifts between stable parties and instability in parties, such as mergers, splinters or new parties), this article introduces a new indicator of electoral instability in parties, tests its robustness and construct validity and demonstrates its usefulness empirically. The indicators of party instability and the accompanying data of 27 European democracies, 1987–2011, will be valuable resources in comparative research on the interplay between elite and mass behavior, party and electoral systems, and democratic consolidation.

The possibility that actors strategically condition their behavior on partially unobservable factors poses a grave challenge to causal inference, particularly if only some of the actors whose behavior we analyze are at risk of experiencing the outcome of interest. We present a crisis bargaining model that indicates that targets can generally prevent war by arming. We then create a simulated data set where the model is assumed to perfectly describe interactions for those states engaged in crisis bargaining, which we assume most pairs of states are not. We further assume researchers cannot observe which states are engaged in crisis bargaining, although observable variables might serve as proxies. We demonstrate that a naïve design would falsely (and unsurprisingly) indicate a positive relationship between arming and war. More importantly, we then evaluate the performance of matching, instrumental variables, and statistical backwards induction. The latter two show some promise, but matching fares poorly.

This article challenges Fixed Effects (FE) modeling as the ‘default’ for time-series-cross-sectional and panel data. Understanding different within and between effects is crucial when choosing modeling strategies. The downside of Random Effects (RE) modeling—correlated lower-level covariates and higher-level residuals—is omitted-variable bias, solvable with Mundlak's (1978a) formulation. Consequently, RE can provide everything that FE promises and more, as confirmed by Monte-Carlo simulations, which additionally show problems with Plümper and Troeger's FE Vector Decomposition method when data are unbalanced. As well as incorporating time-invariant variables, RE models are readily extendable, with random coefficients, cross-level interactions and complex variance functions. We argue not simply for technical solutions to endogeneity, but for the substantive importance of context/heterogeneity, modeled using RE. The implications extend beyond political science to all multilevel datasets. However, omitted variables could still bias estimated higher-level variable effects; as with any model, care is required in interpretation.

This article introduces a model of war and peace in which leaders believe that their adversaries might be crazy types who always behave aggressively, regardless of whether it is strategically optimal to do so. In the model, two countries are involved in a dispute that can either end in a peaceful settlement or escalate into ‘limited war’ or ‘total war.’ If it is common knowledge that the leaders of the countries are strategically rational, then the only equilibrium outcome of the model is peace. Yet if a leader believes that there is a chance that her adversary is a crazy type, then even a strategically rational adversary may have an incentive to adopt a madman strategy in which he pretends to be crazy. This leads to limited war with positive probability, even when both leaders are strategically rational. The article shows that despite having two-sided incomplete information, the model has a generically unique equilibrium. Moreover, the model identifies two countervailing forces that drive equilibrium behavior: a reputation motive and a defense motive. When the prior probability that a leader is crazy decreases, the reputation motive promotes less aggressive behavior by that leader, while the defense motive pushes for more aggressive behavior. These two forces underlay several comparative statics results. For example, the study analyzes the effect of increasing the prior probability that a leader is crazy, and the effect of changing the relative military strengths of the countries, on the equilibrium behavior of both leaders. The analysis also characterizes the conditions under which the madman strategy is profitable (or not), which contributes to the debate in the literature about its effectiveness.

I develop a theory of the emergence of minority and majority governments in multiparty parliamentary systems. I study a general bargaining environment with a policy space of arbitrary finite dimension, any number of political parties, and a general class of preferences over the government agreement space. I find that only majority governments form in the absence of significant political disagreement. However, I show that, except for knife-edge situations, minority government are formed with positive probability when parties represented in parliament are sufficiently ideologically polarized.

What factors make it more likely that non-state organizations will target civilians as a political strategy? This study examines targeting civilians as a tactical and normative choice, and hypothesizes that the targeting of civilians (compared to the general use of violence) is a function of the ideological make-up of organizations, organization weakness and state repression. Other factors related to organizational capability will not have a differential impact on the likelihood that an organization will target civilians for violence. This article uses data from the Minorities at Risk Organizational Behavior database to examine these issues with respect to ethno-political organizations. It argues that the typical analytic focus on general violence obscures understanding of the factors that lead to targeting civilians. It finds that targeting civilians—while similar in some respects to the use of general violence—is different, particularly with respect to organizational ideology.

What would Israel’s economy have looked like without the 2000 Palestinian Intifada? This article examines this counterfactual question by statistically comparing the economic growth trajectories of Israel and a “synthetic” Israel, which is constructed by applying a method proposed by Abadie and Gardeazabal (2003) and Abadie, Diamond and Hainmueller (2010, 2014). The results of the analysis suggest that Israel’s per capita gross domestic product during the Second Intifada was reduced by an average of about $2,003 per year (in 2005 US dollars). This amounts to about 8.6 percent of the 2000 baseline level. In the case of the Second Intifada, the opportunity cost of conflict was indeed substantial and significant.

The European sovereign debt crisis continues to hold Europe and the world captive. Will the euro and the fiscal mechanism of the eurozone survive? And how effective is the Stability and Growth Pact (SGP)? Do the euro countries generally fail to comply with the rules of fiscal governance, or does the eurozone need a more member-specific fiscal mechanism? This article examines whether and how the SGP influenced the development of government debt making in the euro countries after the introduction of the common currency. While the SGP could not prevent euro countries from exceeding their deficits, this study’s synthetic control analysis reveals that the mechanism has effectively reduced the overall government debt of euro countries since 1999. In particular, donor countries were able to control governmental spending, while many recipient countries—including Greece, Portugal and Italy—have increased government debt ever since, resulting in the European sovereign debt crisis. This suggests that while the SGP effectively constrained overall government debt making, a more sophisticated mechanism is required for safeguarding compliance in large recipient countries.

Governments’ party identifications can indicate the types of economic policies they are likely to pursue. A common rule of thumb is that left-party governments are expected to pursue policies for lower unemployment, but which may cause inflation. Right-party governments are expected to pursue lower inflation policies. How do these expectations shape the inflation forecasts of monetary policy bureaucrats? If there is a mismatch between the policies, bureaucrats expect governments to implement, and those that they actually do, forecasts will be systematically biased. Using US Federal Reserve Staff’s forecasts we test for executive partisan biases. We find that irrespective of actual policy and economic conditions forecasters systematically overestimate future inflation during left-party presidencies and underestimate future inflation during right-party ones. Our findings suggest that partisan heuristics play an important part in monetary policy bureaucrats’ inflation expectations.

A large class of spatial models of elections converges upon a single prediction: a candidate’s vote share increases in the congruence between her platform and the median voter’s preferences. Though considerable empirical research provides support for this prediction, these studies have not adequately identified the effects of platform positioning net of other factors. In this paper, we study the impact of challenger moderation on vote shares using data from 444 US House elections from 1996 to 2006 in which successive challengers competed against a common incumbent. Our findings are largely null. We uncover no evidence that challengers increase their vote shares by adopting more moderate platform positions. This finding is robust across a wide range of model specifications and subsets of districts.

The logic of historical explanation obliges one to understand temporality as a moderator of various effects on political outcomes. Temporal problems remain in the empirical analysis of political phenomena, however, especially as it pertains to categorical data and long-term time dependence. Many theories in political science assert that sequencing matters or that political outcomes are path dependent, but they remain untested (or improperly tested) assertions for which sequence analysis may be valuable. This article briefly reviews the disciplinary origins of sequence analysis and applies the method in order to understand bargaining between actors during national crises. Finally, it explores the robustness of a commonly used sequence analysis metric. The ability to demonstrate and separate sequential effects from accumulative effects—made possible through sequence analysis—constitutes a major step in political science toward analyses that are truly time sensitive.

Party identification and issue preferences are central explanatory factors in many voting choice models. Their effects on party preferences are usually understood to be additive. That is, issue preferences’ impact on party utilities is assumed to be the same among both party identifiers and nonidentifiers. This article suggests an alternative model in which party identification moderates the impact of issues on the vote. The impact of issue preferences on party utilities should be weaker among voters who identify with a party. This hypothesis is tested using data from four recent Dutch election studies. The results show that identifying with a party substantially weakens the issue preference effect on party evaluations, particularly for the party with which a voter identifies.

Scholars studying opinion representation often rely on a survey question that asks about the “most important problem” (MIP) facing the nation. While it is known that MIP responses reflect public priorities, less is known about their connection to policy preferences. This article directly addresses the issue. First, it conceptualizes policy preferences and MIP responses, specifically considering the possibility that the latter may be either policy or outcome based. Second, using aggregate-level data from the United States and the United Kingdom, it then examines the correspondence between public spending preferences and MIP responses over time. The results indicate that MIP responses and spending preferences tap very different things, and that using MIP responses substantially understates the representational relationship between public opinion and policy.

Empirical analyses in social science frequently confront quantitative data that are clustered or grouped. To account for group-level variation and improve model fit, researchers will commonly specify either a fixed- or random-effects model. But current advice on which approach should be preferred, and under what conditions, remains vague and sometimes contradictory. This study performs a series of Monte Carlo simulations to evaluate the total error due to bias and variance in the inferences of each model, for typical sizes and types of datasets encountered in applied research. The results offer a typology of dataset characteristics to help researchers choose a preferred model.

A large literature argues that public opinion is vulnerable to various types of framing and cue effects. However, we lack evidence on whether existing findings, which are typically based on lab experiments involving low-salience issues, travel to salient and contentious political issues in real-world voting situations. We examine the relative importance of issue frames, partisan cues, and their interaction for opinion formation using a survey experiment conducted around a highly politicized referendum on immigration policy in Switzerland. We find that voters responded to frames and cues, regardless of their direction, by increasing support for the position that is in line with their pre-existing partisan attachment. This reinforcement effect was most visible among low knowledgeable voters that identified with the party that owned the issue. These results support some of the previous findings in the political communication literature, but at the same time also point toward possible limits to framing effects in the context of salient and contested policy issues.

Africa’s arbitrary country borders have been seized upon as sources of “natural experiments”: having randomly assigned people to different country treatments, differences in outcomes on either side of the border can then be attributed to the institutions, demographics, or policies put in place in each country. While methodologically attractive, the use of African borders as sources of natural experiments presents several potential pitfalls. We describe these pitfalls—some common to all studies that employ jurisdictional boundaries, some unique to African borders—and offer guidelines for overcoming them. We conclude that African cross-border studies can provide research advantages similar to well-executed comparative case studies, but that they frequently offer weaker inferential leverage than is claimed.