Democratic accountability relies on voters to punish their representatives for policies they dislike. Yet, a separation-of-powers system can make it hard to know who is to blame, and partisan biases further distort voters’ evaluations. During the COVID-19 pandemic, precautionary policies were put into place sometimes by governors, sometimes by mayors, and sometimes by no one at all, allowing us to identify when voters hold out-party versus in-party politicians responsible for policies. With a survey spanning 48 states, we test our theory that attitudes toward policies and parties intersect to determine when selective attribution takes place. We find that as individuals increasingly oppose a policy, they are more likely to blame whichever level of government is led by the out-party. This is most pronounced among partisans with strong in-party biases. We provide important insight into the mechanisms that drive selective attribution and the conditions under which democratic accountability is at risk.

Communication is a fundamental step in the process of political representation, and an influential stream of research hypothesizes that male and female politicians talk to their constituents in very different ways. To build the broad dataset necessary for this analysis, we harness the massive trove of communication by American politicians through Twitter. We adopt a supervised learning approach that begins with the hand coding of over 10,000 tweets and then use these to train machine learning algorithms to categorize the full corpus of over three million tweets sent by the lower house state legislators who were serving in the summer of 2017. Our results provide insights into politicians’ behavior and the consequence of women’s underrepresentation on what voters learn about legislative activity.

Legislators must decide when, if ever, to cosponsor legislation. Scholars have shown legislators strategically time their positions on salient issues of national importance, but we know little about the timing of position-taking for routine bills or what this activity looks like in state legislatures. We argue that legislators’ cosponsorship decision-making depends on the type of legislation and the partisan dynamics among the current cosponsors. Members treat everyday legislation as generalized position-taking motivated by reelection, yet for key legislation, legislators are policy-oriented. With a new dataset of over 73,000 bills introduced in both chambers of the Texas state legislature in the 75th to 86th regular sessions (1997–2020), we use pooled Cox proportional hazard models to evaluate the dynamics of when legislators legislate, comparing all bills introduced with a subset of key bills. The results show that legislators time their cosponsorship activity in response to electoral vulnerability, partisanship, and the dynamics of the chamber in which they serve.

The scholarly exchange over approaches to measuring public preferences in the American states dates back several years. This introduction to the debate attempts to provide broad perspective on how scholars have conceptualized and measured policy mood among state mass publics in the past and the implications of those choices for theoretical and empirical questions in state politics. We frame the discussion around two questions: (1) what is the concept to be measured? and (2) how does the concept fit with the research question? We conclude with some insight on the future of the debate and its implications for state politics research.

Enns and Koch question the validity of the Berry, Ringquist, Fording, and Hanson measure of state policy mood and defend the validity of the Enns and Koch measure on two grounds. First, they claim policy mood has become more conservative in the South over time; we present empirical evidence to the contrary: policy mood became more liberal in the South between 1980 and 2010. Second, Enns and Koch argue that an indicator’s lack of face validity in cross-sectional comparisons is irrelevant when judging the measure’s suitability in the most common form of pooled cross-sectional time-series analysis. We show their argument is logically flawed, except under highly improbable circumstances. We also demonstrate, by replicating several published studies, that statistical results about the effect of state policy mood can vary dramatically depending on which of the two mood measures is used, making clear that a researcher’s measurement choice can be highly consequential.

In the face of the intensifying global climate crisis, the US has failed to implement comprehensive policies to mitigate greenhouse gas emissions. During the 2000s, the shale oil and gas extraction (i.e., “fracking”) revolution highlighted the American energy economy. Is the fracking boom partially to blame for US lagging on climate policy? Political economy theory suggests that economic resources are primary drivers of policy outcomes. In this paper, I originally evaluate that claim in the context of the American states, the governments most powerful to mitigate emissions while the federal government faces gridlock. I first introduce an original measure of one state-level climate policy: adoption of the low-emission vehicle (LEV) policy from 1991 to 2015. I then frame the US fracking boom of the mid-to-late 2000s as a natural experiment, employing a difference-in-difference design to compare the effects of fracking on two climate policies across the American states – LEV and renewable electricity policy. Results yield evidence of a causal impact of the fracking boom on state LEV adoption and more suggestive evidence of an impact on renewable electricity mandates. I conclude by arguing that efforts to evaluate the influence of business on policy should account for “structural power” mechanisms.

Why have some states adopted policies expanding ballot access while others have restricted access to the ballot? Since the 1990s, some states have been adopting policies restricting access to the ballot such as requiring identification. At the same time, states have been adopting a variety of registration reforms that lower the barriers to registration and voting. Using an original, 45-state dataset, we examine state innovation within the policy domain of electoral reforms in US states. We find reforms have an independent and, sometimes, negative effect on the innovation of states in electoral reforms. Next, we use dyad analysis to examine the spread of a single policy: automatic voter registration. We find that the propensity to innovate both within and across a state makes the spread of automatic voter registration more likely. Our paper contributes to the broader understanding of why states adopt electoral reforms.

We examine how institutional selection procedures affect the ideology of state supreme court chief justices. We argue that institutional selection methods empower those charged with choosing chief justices to select court leaders who reflect their own preferences, and we test this theory using data from all 50 American states from 1970 to 2017. Our results show that states that use popular elections to select chief justices tend to produce court leaders whose preferences reflect the electorate, and states that use commission-assisted elite appointment tend to produce chief justices whose preferences mirror those of political elites. While we find that peer election systems produce leaders with preferences similar to median court preferences, court preferences are also associated with other methods of chief justice selection.

The Internet has spawned a renewed hope for facilitating increased access to candidate information for voters. However, the nationalization and polarization of constituents have left many candidates averse to the risks of personalized campaigns, especially in subnational elections. Under what conditions are state candidates willing to establish a personalized web presence as opposed to relying on partisanship? This study introduces a novel dataset of campaign website presence for the 2018 and 2020 state legislative elections. During this time, approximately one-third of state legislative candidates opted to forgo a personalized campaign website. District-level constituent ideology was significantly correlated with the website use, even when controlling for district education, income, age, and race, and the candidate’s competitive position. District ideological homogeneity encouraged website use across both parties, while adversarial district ideology corresponded to low website use among Republicans. The results indicate that state legislative candidates, especially Republican candidates, are far more likely to preach to their partisan choir rather than incur the risks of proselytizing among their partisan opposition. The results reiterate the divergent responses of the political parties regarding partisan polarization and shed light on the impact of nationalization within state legislative campaigns.

Do reserved seats yield substantive representation for traditionally marginalized groups? To answer that question, we turn to a remarkable and little-studied institution: reserved seats for Native American tribes in the Maine House of Representatives. Tribal representatives, who can participate in debate but lack a vote, have represented tribes in Maine’s House of Representatives since statehood in 1820. We take advantage of a 1995 rule change that allowed tribal representatives to initiate legislation, and an original dataset of pro-tribal bills, to estimate the effect of reserved seats on the production of pro-tribal bills. We find that once tribal representatives were allowed to write bills, they produced over half of all tribal-related legislation during a 36-year period. Legislators with tribal constituents sponsored fewer relevant bills after the reform but continued to cosponsor pro-tribal legislation. Although our results show tribal representatives contribute to the legislative process, we caution that reserved seats are not a panacea for improving Indigenous representation.

To fully understand state policy outcomes or elections in the US, we need valid over-time measures of state-level public opinion. We contribute to the research on measuring state public opinion in two ways. First, we respond to Berry, Fording, Hanson, and Crofoot’s (BFHC) critique of Enns and Koch’s measure of state policy mood. We show that when BFHC’s analysis is performed using the same states and examining annual change, it validates the Enns and Koch measure and raises questions about the Berry, Ringquist, Fording, and Hanson measure. Second, we generate a new measure of state policy mood building on Enns and Koch’s approach. The new measure has even better properties than the previous measure and relates to state presidential vote and state policy liberalism in similar ways to Caughey and Warshaw’s measure of state economic liberalism. We conclude with recommendations for using the various direct measures of state public opinion.

This study uses prediction market data from the nation’s historical election betting markets to measure electoral competition in the American states during the era before the advent of scientific polling. Betting odds data capture ex ante expectations of electoral closeness in the aggregate, and as such improve upon existing measures of competition based on election returns data. Situated in an analysis of the 1896 presidential election and its associated realignment, I argue that the market odds data show that people were able to anticipate the realignment and that expectations on the outcome in the states influenced voter turnout. Findings show that a month ahead of the election betting markets accurately forecast a McKinley victory in most states. This study further demonstrates that the market predictions identify those states where electoral competition would increase or decline that year and the consequences of these expected partisanship shifts on turnout. In places where the anticipation was for a close race voter expectations account for a turnout increase of as much as 6%. Participation dropped by 1%–6% in states perceived as becoming electorally uncompetitive. The results support the conversion and dealignment theories from the realignment literature.

Among US states with party registration, many allow the unaffiliated to choose either the Democratic or Republican primary. States with these semi-closed rules thus provide an option to voters with greater choice than registering with a single political party. Using the synthetic control method, I find that the introduction of semi-closed primaries is associated with growth in unaffiliated registration. However, the likelihood of unaffiliated registration is not even across the electorate in semi-closed states. I show that it is most common where a voter’s party is not competitive and the access unaffiliated registration provides to the strong party’s primary is valuable. Consistent with this instrumental motive, unaffiliated voters in semi-closed states use their freedom of choice to vote in the primary of the stronger party in the electorate. This leads to significant crossover voting among unaffiliated voters who do not identify with that party such as Democrats in red states or Republicans in blue states. These findings show the unintended consequences of electoral institutions and find primary crossover voting is more common under some circumstances than others.

This article presents a short summary of the conclusions we report in a longer manuscript (available in our Supplementary Material) subjecting Lagodny et al.’s new measure of state policy mood to the same set of face validity and construct validity tests we applied earlier to Enns and Koch’s measure. We encourage readers to read this longer manuscript, which contains not only the conclusions herein, but also the evidence justifying these conclusions, before accepting or rejecting any claims we make. Our results show that the characteristics of Enns and Koch’s measure that led us to be doubtful that it is valid are also present in Lagodny et al.’s new measure – leaving us just as doubtful that Lagodny et al.’s measure is valid. Moreover, the low correlation between Lagodny et al.’s measure and Enns and Koch’s measure, combined with evidence from replications of seven published studies that the two measures frequently yield quite different inferences about the impact of policy mood on public policy, indicate that Lagodny et al.’s claim that both their measure and Enns and Koch’s measure are valid is wrong; either neither measure is valid, or one is valid and the other is not. Moreover, extending the replications to include not only Lagodny et al.’s and Enns and Koch’s measures, but also Berry et al.’s measure and Caughey and Warshaw’s measure of mass economic liberalism, shows that each of the four measures yields a substantive conclusion about the effect of policy mood that is dramatically different than each of the other three measures. This suggests that the goal of developing a measure of state policy mood that would be widely accepted as valid remains elusive.

This article introduces the State Executive Approval Database, a dataset of gubernatorial approval ratings that updates and adds to data previously collected by Beyle et al. In addition to the survey marginals, the dataset presents continuous quarterly and annual measures of the latent level of governor approval that are amenable for time series analysis. After evaluating how survey data availability varies across states and over time, I use the data to evaluate whether governors receive a honeymoon. While new governors do not have higher than expected levels of approval, the public expresses comparatively low levels of disapproval for new governors. This honeymoon is largely restricted to their first quarter in office and only occurs when they are elected to their first term. Governors who take office after their predecessor resigned get a slightly longer and more sustained reprieve from disapproval. Governor approval is also significantly shaped by unemployment levels in their state. These data will provide scholars with new opportunities to study accountability and representation at the state level.

How representative are conference delegations in state legislative chambers? I argue that differing conference rules across state legislative chambers influence majority party control over conference delegations. With an original data set encompassing all state-level conference committees from 2005 to 2016, I compare the observed policy preferences between conference delegation and majority party medians when the majority party unilaterally appoints and when the minority party has influence over conferee selection. My results show that in state legislative chambers where the minority can influence conference appointments, delegations are ideologically biased away from the majority party. These findings underscore how majority parties are limited when minorities have procedural rights.

Identifying the geographic constituencies of representatives is among the most crucial, yet challenging, aspects of state and local politics research. Regularly changing district lines, incomplete data, and computational obstacles can present barriers to matching individuals to their respective districts. Geocoding residential addresses is the ideal method for matching purposes. However, cost constraints can limit its applicability for many researchers, leading to geographic assignment methods that use polygonal units, such as ZIP codes, to estimate constituency membership. In this study, we quantify the trade-offs between three geographic assignment matching methods – centroid, geographic overlap, and population overlap matching – on the assignment of individual voters to state legislative districts. We confirm that population overlap matching produces the highest accuracy in assigning voters to their state legislative districts when polygonal location data are all that is available. We validate this finding by improving model estimates of lobbying influence through a replication analysis of Bishop and Dudley (2017), “The Role of Constituency, Party, and Industry in Pennsylvania’s Act 13,” State Politics and Policy Quarterly 17 (2): 154–79. Our replication suggests that distinguishing between out-of-district and in-district donations reveals a greater impact for in-district lobbying efforts. We make evident that population overlap assignment can confidently be used to identify constituencies when precise location data is not available.

This article concludes an exchange on developing and improving longitudinal estimates of state-level public opinion in the United States by introducing the U.S. Partisanship and Presidential Approval Dataset, which combines more than 1.1 million survey responses from 1948 to 2020 into a single harmonized “mega poll.”

Evidence suggests that well-funded, professional legislatures more effectively provide constituents with their preferred policies and may improve social welfare. Yet, legislative resources across state legislatures have stagnated or dwindled at least in part due to public antagonism toward increasing representatives’ salaries. We argue that one reason voters oppose legislative resources, like salary and staff, is that they are unaware of the potential benefits. Employing a pre-registered survey experiment with a pre–post design, we find that subjects respond positively to potential social welfare benefits of professionalization, increasing support for greater resources. We also find that individuals identifying with the legislative majority party respond positively to potential responsiveness benefits and that out-partisans do not respond negatively to potential responsiveness costs. In a separate survey of political elites, we find similar patterns. These results suggest that a key barrier to increasing legislative professionalism – anticipated public backlash – may not be insurmountable. The findings also highlight a challenge of institutional choice: beliefs that representatives are unresponsive or ineffective lead to governing institutions that may ensure these outcomes.

Executives are important elites, and ideology is important to elite behavior, but measurement challenges and a focus on the presidency have kept scholars from fully exploring executive ideology. This article advocates studying US governors to learn more about executive ideology. It provides an overview of the data scholars can use to measure gubernatorial preferences, and highlights Bonica’s campaign finance-based ideology scores (CFscores) as offering the greatest coverage and allowing common-scale comparisons with other actors. As a validation exercise, I find that CFscores explain within-party variation in other measures and predict the decisions that governors make when in office. Then, I run a preliminary test of the substantive importance of executive ideology. Four models explain state policy liberalism as a function of executive, legislative, and citizen ideology. Gubernatorial preferences emerge as most predictive of the three. These results encourage greater investigation into the role of executive ideology in the policy process.