In this article, I revisit a widely used measure of legislative professionalism that I developed over a decade ago (Squire 1992a). I argue that professionalism has different implications for legislators than for legislatures and that the concept is distinct from careerism. I then discuss the mechanics of compiling the measure, its reliability and validity, and potential criticism of the measure. Finally, I provide scores on the measure for 1979, 1986, 1996, and 2003, as well as scores for 1979 and 2003 for a revised measure that is theoretically appropriate for use in dynamic analyses.

Berry et al.'s (1998) measures of U.S. state citizen and government ideology rely on unadjusted interest-group ratings for a state's members of Congress to infer information about (1) the ideological orientation of the electorates that selected them or (2) state legislators and the governor from the same state. Potential weaknesses in unadjusted interest-group ratings prompt the question: Are the Berry et al. measures flawed, and if so, can they be fixed by substituting alternative measures of a member's ideology? We conclude that a version of the Berry et al. state government ideology indicator relying on NOMINATE common space scores is marginally superior to the extant version. In contrast, we reaffirm the validity of the original state citizen ideology indicator and find that versions based on NOMINATE common space scores and adjusted ADA and COPE scores introduced by Groseclose, Levitt, and Snyder (1999) are weaker.

Researchers are often interested in the effects of state policies and institutions on individual behavior or other outcomes in sub-state-level observational units, such as election results in state legislative districts. In this article, we examine the issue of clustered data in state and local politics research and the analytical problems it can cause. Standard estimation methods applied in most regression models do not properly account for the clustering of observations within states, leading analysts to overstate the statistical significance of coefficient estimates, especially of state-level factors. We discuss the theory behind two approaches for dealing with clustering—clustered standard errors and multilevel modeling—and argue that calculating clustered standard errors is a more straightforward and practical approach, especially when working with large datasets or many cross-level interactions. We demonstrate the relevance of this topic by replicating a recent study of the effects of state post-registration laws on voter turnout (Wolfinger, Highton, and Mullin 2005).

This article analyzes existing scholarship on the diffusion of public policies among the American states, focusing on recent developments in this line of research and suggesting several potential avenues for future work. The analysis is organized around three fundamental questions. First, why does policy diffusion occur? Answering this question will require scholars to devote more attention to concepts such as imitation, emulation, and competition. Second, which political forces facilitate or impede policy diffusion? Answering this question will require scholars to devote more attention to the causal mechanisms at work when states adopt policies like those of other states. Third, what is being diffused? Answering this question will require scholars to think more carefully about the content of public policy, both as an outcome to be explained and as a factor that itself affects the diffusion process.

In 1996, more than half of the states considered legislation banning same-sex marriages. This article examines these events as a geographic expansion of the scope of the conflict rather than as traditional state-centered policy innovation. I argue that the diffusion of same-sex marriage bans was determined by the organized efforts of advocacy coalitions and internal state characteristics rather than by regional diffusion or communication among policy experts. I use state-level data collected from activists, media accounts, and official sources to establish the organized efforts to ban same-sex marriage. I then develop and empirically test a model of policy diffusion to predict both state consideration and adoption of policies banning same-sex marriage. The findings suggest that the diffusion of these policies is best explained by the presence of an organized national campaign by conservative religious groups, the local resources of interest groups, and other internal state characteristics rather than by regional diffusion patterns. I also find that the influence of state characteristics may vary during the policymaking process.

We use a survey of State House reporters to measure corruption in state government and assess the priority federal prosecutors place on corruption investigations. The reliability and validity of the corruption measures are assessed, as are the relationships among corruption level, federal prosecutorial effort, and the number of federal prosecutions. Federal corruption prosecutions are positively correlated with both corruption and prosecutorial effort. Hence, we argue that federal prosecution data provide a potentially biased and unreliable measure of state public corruption.

What is the impact of direct democracy on citizens' political participation and knowledge? Progressive Era reformers and normative theorists have argued that institutional procedures allowing citizens a more direct role in government decision-making will increase civic engagement, broadly defined. Using American National Election Studies data for 1996, 1998, and 2000, we test this hypothesis. Our multivariate analysis suggests that exposure to ballot initiatives increases the probability of voting, stimulates campaign contributions to interest groups, and enhances political knowledge. However, we find that the impact of the initiative process on political participation and knowledge varies with electoral context.

The measure of legislative professionalization I developed was first published a quarter century ago. Since then, updates have appeared periodically. In this note, I briefly document the measure's usefulness in academic research and then calculate it for 2015. For reasons I detail, the updated measure is corrected for a misestimate of days in session for some states.

How do the American states vary in their propensity for innovativeness, or their willingness to adopt new policies sooner or later relative to other states? Most studies today use event history analysis (EHA) to focus almost exclusively on one policy area at a time at the expense of a broader understanding of innovativeness as a characteristic of states. To return to the concept of innovativeness more broadly, our study revisits and updates the original approach taken by Walker by updating his average innovation scores with new data covering more than 180 different policies. We use these data to construct a new, dynamic measure of innovativeness that addresses biases and shortcomings in the original measure and we provide measures of uncertainty for both. These new scores build on the logic of EHA to address issues such as right-censoring and to facilitate measuring changes in innovativeness over time. We then compare the two measures of innovativeness and evaluate differences across states, spatial patterns, and changes in innovativeness over time.

This note examines problems associated with measuring the partisan balance of state government. A description of a new publicly available dataset is given, as well as of the methods used to collect these data. The results of three data analyses using different measures of state government partisan balance demonstrate that sometimes measurement error on this variable can influence substantive findings.

This article puts forward four strategies to improve policy diffusion research in political science: (1) use existing concepts consistently and improve their measurement, (2) clarify whether the goal is to improve the understanding of diffusion itself or to use diffusion research to explain another phenomenon, (3) pay more attention to the quality of the research design, and (4) discuss explicitly the practical implications of diffusion. Taken together, these recommendations trace a distinctive way forward for policy diffusion research.

The national government can force or entice state governments to act on policy through a variety of actions, including providing monetary incentives and sanctions. We examine how and under what conditions actions of the national government influence the diffusion of policy across the states. We test our hypotheses on the cases of the diffusion of partial birth abortion laws, truth-in-sentencing laws, and hate crime laws using event history analysis on pooled cross-sectional data from the 50 states. Our results suggest that, in addition to fiscal incentives, the national government can influence state policymaking when it sends strong, clear signals to the states concerning its preferences and the potential for future action. But even national-level signals that are weak and ambiguous may influence state policymaking indirectly.

Legislative professionalism has played a prominent role in state politics research for decades. Despite the attention paid to its causes and consequences, recent research has largely set aside questions about professionalism's conceptualization and operationalization. Usually measuring it as an aggregate index, scholars theoretically and empirically treat professionalism as a unidimensional concept. In this article, we argue that exclusive use of aggregate indices can limit state politics research. Using a new dataset with almost 40 years of data on state legislative resources, salary, and session length, we reconsider the validity of using an index to study professionalism across the states. We evaluate the internal consistency of professionalism components over time, the relationship between components and the Squire Index, and the degree to which professionalism components are unidimensional using classical multidimensional scaling. We find enough commonality and enough variation between professionalism components to support a range of measurement strategies like the use of unidimensional indices (such as the Squire Index), disaggregating the components and analyzing their effects individually, or formulating multidimensional measures. Scholars should take care to choose the appropriate measure of the concept that best fits the causal relationships under examination.

We explore the effect of the transparency of fiscal institutions in government on the scale of government and gubernatorial approval using a formal model of accountability. We construct an index of fiscal transparency for the American states from detailed budgetary information. With cross-sectional data for 1986-95, we find that—on average and controlling for other factors—fiscal transparency increases both the scale of government and gubernatorial approval. Our results imply that more transparent fiscal institutions induce greater effort by politicians, to whom voters give higher job approval, on average. Voters also respond by entrusting greater resources to politicians where fiscal institutions are more transparent, leading to larger government.

Numerous studies attempt to assess direct democracy's impact on state policy using measures of direct democracy based on dummy variables or the frequency with which initiatives appear on a state's ballots. We offer an alternative to these measures that accounts for how rules governing the initiative process vary among the states. We replicate several studies using different measures of direct democracy and demonstrate that the results of hypothesis tests can be contingent on how these institutions are measured. We contend that commonly used dummy variable measures of state direct democracy have validity problems and that hypothesis tests using such measures produce imprecise estimates of the initiative's effect on policy.

In this article, we create, validate, and analyze new dynamic measures of state partisanship, state policy mood, and state political ideology. The measures of partisanship and policy mood begin in 1956 and the measure of ideology begins in 1976. Our approach uses the advantages of two leading techniques for measuring state public opinion—multilevel regression and poststratification (MRP) and survey aggregation. The resulting estimates are based on nearly 500 different surveys with a total of more than 740,000 respondents. After validating our measures, we show that during the last half century, policy preferences in the states have shifted in important and sometimes surprising ways. For example, we find that differences in political attitudes across time can be as important as differences across states.

In November 1996, voters cast ballots for candidates running for 57 seats on 15 community advising and zoning boards in Miami-Dade County, Florida. Voters had little knowledge about the candidates or the boards that had been created only a few months earlier. The candidates campaigned for seven weeks. The local media generally ignored them. There were no incumbents and no party labels in the non-partisan contests. In low-information local elections such as these, voter cues and ballot design plays a decisive role in voter choice. The cues in this election were candidates' gender, ethnicity, campaign expenditures, and ballot position. Our results indicate that the most important cue was candidate gender; however, voters used ethnicity to decide whether they voted for men or women. The number of candidates on the ballot impacted vote share, while ballot position played no significant role. Those candidates who spent the most campaign money were also preferred. We argue that vote cues provide a means to address voter fatigue, where gender, ethnicity, and name recognition provide cues in this low-information, high voter fatigue situation. Our results suggest that by spending greater on their campaigns, Hispanic women—the most disadvantaged of the candidates—could run competitively against Hispanic men.

Since 1990, the standard statistical approach for studying state policy adoption has been an event history analysis using binary link models, such as logit or probit. In this article, we evaluate this logit-probit approach and consider some alternative strategies for state policy adoption research. In particular, we discuss the Cox model, which avoids the need to parameterize the baseline hazard function and, therefore, is often preferable to the logit-probit approach. Furthermore, we demonstrate how the Cox model can be modified to deal effectively with repeatable and competing events, events that the logit-probit approach cannot be used to model.

Despite the bias against such studies in our discipline, we argue that research designs focusing on a single state are sometimes preferable to those employing data from all 50 states. Single state studies are appropriate when the researcher wishes to generalize to a unit of analysis other than the states themselves, when conditions in a given state provide a unique opportunity for the most rigorous test of a hypothesis, and when the measurement advantages of a single-state study outweigh the costs of limited generalization. We draw on a range of literature to reinforce our primary contention, that it is soundness of theory and rigor of analysis, rather than the number of states, that makes research valid and important.

Can voters stop state governments from spending at high rates through the enactment of tax and expenditure limits (TELs), or do these laws become dead letters? We draw upon the principal-agent literature to theorize that TELs—one of the most frequent uses of the initiative process across the country—might be circumvented by the sorts of elected officials who would inspire their passage. We test for the effectiveness of TELs across states using a differences-in-differences model. Second, we decompose our treatment variable using different legal provisions of the limits to test whether there is a uniform effect across different types of TELs. Finally, we compare state fiscal patterns before and after adoption on a state-by-state basis. Using these approaches and other methods, we show that TELs are largely ineffective and that state officials can circumvent them by raising money through fees. Our finding is consistent with recent studies showing that policies passed through direct democracy can often be thwarted by the politicians charged with implementing them.