Sensitive survey techniques (SSTs) are frequently used to study sensitive behaviors. However, existing strategies for employing SSTs lead to highly variable prevalence estimates and do not permit analysts to address the question of whether the use of an SST is actually necessary. The current article presents a survey questioning strategy and corresponding statistical framework that fills this gap. By jointly analyzing survey responses generated by an SST (the crosswise model) along with direct responses about the sensitive behavior, the article's framework addresses the question of whether the use of an SST is required to study a given sensitive behavior, provides an efficient estimate of the prevalence of the sensitive behavior, and, in its extended form, efficiently estimates how individual characteristics relate to the likelihood of engaging in the behavior. The utility of the approach is demonstrated through an examination of gender differences in proclivities towards corruption in Costa Rica.

Political scientists increasingly use instrumental variable (IV) methods, and must often choose between operationalizing their endogenous treatment variable as discrete or continuous. For theoretical and data availability reasons, researchers frequently coarsen treatments with multiple intensities (e.g., treating a continuous treatment as binary). I show how such coarsening can substantially upwardly bias IV estimates by subtly violating the exclusion restriction assumption, and demonstrate that the extent of this bias depends upon the first stage and underlying causal response function. However, standard IV methods using a treatment where multiple intensities are affected by the instrument–even when fine-grained measurement at every intensity is not possible–recover a consistent causal estimate without requiring a stronger exclusion restriction assumption. These analytical insights are illustrated in the context of identifying the long-run effect of high school education on voting Conservative in Great Britain. I demonstrate that coarsening years of schooling into an indicator for completing high school upwardly biases the IV estimate by a factor of three.

Existing methods for estimating ideal points of legislators that are comparable across time and chambers make restrictive assumptions regarding how legislators' ideal points can move over time, either by fixing some legislators' ideal points or by constraining their movement over time. These assumptions are clearly contradictory to some theories of congressional responsiveness to election dynamics and changes in constituency. Instead of using legislators as anchors, our approach relies on matching roll calls in one chamber and session with roll calls or cosponsorship decisions on identical bills introduced in a different chamber or session. By using these “bridge decisions” to achieve comparability, we can remove any assumptions about the movement of legislators' ideal points. We produce these estimates for both chambers from the 102nd (1991–92) to 111th (2009–11) Congresses, and we show that our estimates provide interesting insights into the nature of legislative behavior change.

Models of ideal point estimation usually build on the assumption of spatial preferences. This ignores legislators' non-policy incentives and is thus likely to produce implausible results for many legislatures. We study this problem in parliamentary systems and develop a model of roll call voting that considers both the policy and the non-policy, tactical incentives of legislators. We go on to show how the relative weight of these policy and tactical incentives is influenced by the identity of the mover and characteristics of the motion. Analyses of two data sets of 2174 roll call votes in German state legislatures and 3295 roll call votes in the British House of Commons result in three main findings. First, we show that tactical incentives may be more important than policy incentives, and second, that the importance of tactical incentives varies with the importance of motions. Third, there are interesting twists: backbench private members' bills may reverse tactical incentives whereas proposals from anti-system parties are virtually always rejected by moderate parties, rendering these votes uninformative. Our findings have implications for ideal point estimation in parliamentary systems, as well as for research on separation of power systems.

Measures of diversity and disparity within a population are used for investigating a range of developmental outcomes, but often by employing “off-the-shelf” indicators that may not be theoretically appropriate for the hypotheses under investigation. In this article, we proposed a general class of social distance measures that both enables us to see the conceptual relationship between different existing measures of heterogeneity more clearly and is sufficiently flexible to allow for the development of tailored hypothesis-specific measures. We show how a range of existing aggregate measures of diversity and disparity fit within the general class and demonstrate illustratively how the measure can be used to develop more precise hypothesis-specific measures.

Guessing on closed-ended knowledge items is common. Under likely-to-hold assumptions, in the presence of guessing, the most common estimator of learning, difference between pre- and postprocess scores, is negatively biased. To account for guessing-related error, we develop a latent class model of how people respond to knowledge questions and identify the model with the mild assumption that people do not lose knowledge over short periods of time. A Monte Carlo simulation over a broad range of informative processes and knowledge items shows that the simple difference score is negatively biased and the method we develop here is unbiased. To demonstrate its use, we apply our model to data from Deliberative Polls. We find that estimates of learning, once adjusted for guessing, are about 13% higher. Adjusting for guessing also eliminates the gender gap in learning, and halves the pre-deliberation gender gap on political knowledge.

A dominant trend in models with binary outcomes is to control for unmodeled duration dependence by including temporal dependence variables. A second, distinct trend is to interpret both the short- and long-term effects of explanatory variables in autoregressive models. While the first trend is nearly ubiquitous in models with binary outcomes, the second trend has yet to be applied consistently beyond models with continuous outcomes. While scholars use temporal splines and cubic polynomials to model the underlying hazard rate, they have neglected the fact that this causes the explanatory variables to have a long-term effect (LTE) by modifying the future values of the temporal dependence variables. In this article, I propose a simple technique that estimates a wide range of probabilistic LTEs in models with temporal dependence variables. These effects can range from simple LTEs for a one-time change in an explanatory variable to more complex scenarios where effects change in magnitude with time and compound across repeated events. I then replicate Clare's (2010, Ideological fractionalization and the international conflict behavior of parliamentary democracies. International Studies Quarterly 54:965–87) examination of the influence of government fractionalization on conflict behavior to show that failing to interpret the results within the context of temporal dependence underestimates the total impact of fractionalization by neglecting LTEs.

In both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geocoded voter registration records. We evaluate the performance of the proposed methodology using approximately nine million voter registration records from Florida, where self-reported ethnicity is available. We find that it is possible to reduce the false positive rate among Black and Latino voters to 6% and 3%, respectively, while maintaining the true positive rate above 80%. Moreover, we use our predictions to estimate turnout by race and find that our estimates yields substantially less amounts of bias and root mean squared error than standard ecological inference estimates. We provide open-source software to implement the proposed methodology.

One of the most robust findings on political institutions is that compulsory voting (CV) reduces the participation gap between poorer and wealthier voters. We present evidence that in Brazil, the largest country to use such a rule, CV increases inequality in turnout. We use individual-level data on 140 million Brazilian citizens and two age-based discontinuities to estimate the heterogeneous effects of CV by educational achievement, a strong proxy for socioeconomic status. Evidence from both thresholds shows that the causal effect of CV on turnout among the more educated is at least twice the size of the effect among those with less education. To explain this result, which is the opposite of what is predicted by the existing literature, we argue that nonmonetary penalties for abstention primarily affect middle- and upper-class voters and thus increase their turnout disproportionately. Survey evidence from a national sample provides evidence for the mechanism. Our results show that studies of CV should consider nonmonetary sanctions, as their effects can reverse standard predictions.

We show how to use multilevel modeling and post-stratification to estimate legislative outcomes under counterfactual representation schemes that, for example, boost the representation of women or translate votes into seats differently. We apply this technique to two research questions: (1) Would the U.S. Congress be less polarized if state delegations were formed according to the principle of party proportional representation? (2) Would there have been stronger support for legalizing same-sex marriage in the U.K. House of Commons if Parliament more closely reflected the population in gender and age?