Current Research

I have two main research interests with American Politics.  The first, within judicial politics, is how collegiality and hierarchy shape and constrain decision making in the U.S. Supreme Court and lower courts.  The second, within distributive politics, is the study of the ways in which both public opinion and U.S. institutions, like parties and apportionment schemes, leave their mark on distributive spending in states and localities.

I am also interested in studying techniques for modeling and analyzing clustered (grouped) data, as many of the causal forces at the core of my substantive inquiries take the form of group-level treatments.

Judicial Politics

Circuit Splits on the U.S. Courts of Appeals. Read more about this project, work in progress, and our data here.

The Circuit Splits Project (with Deborah Beim, University of Michigan) is the first comprehensive study of inter-circuit splits in the U.S. Courts of Appeals, within political science or legal scholarship. Circuits “split” when two or more circuits resolve the same legal question differently, causing similarly-situated litigants in different jurisdictions to be treated differently under the same exact federal law (whether statutory, constitutional, or precedential). Cases involved in splits are widely considered to be the core target cases for Supreme Court review. These cases provide an opportunity to study the relationship between the Supreme Court and circuit courts, the formation of the Supreme Court’s docket, significant changes to the path of law, and the role of ideology in shaping this path. They also allow us to study the strategies of interest groups pursuing policy agendas through litigation.

Americans’ Knowledge of the U.S. Supreme Court with John Bullock.

Abstract: Recent and influential research suggests that political scientists have sharply understated popular knowledge of the U.S. Supreme Court. This research implies that popular knowledge of other aspects of government has been understated as well. The implication may be correct. But these revisionist studies of political knowledge err in the other direction: they overstate popular knowledge of politics. Focusing on the Supreme Court, we use a series of national-sample experiments to show that inferences about popular knowledge of politics depend heavily on little-appreciated aspects of survey design and analysis. Accounting for these aspects of design and analysis suggests a level of knowledge in the polity that lies between the levels suggested by conventional and revisionist research.

Distributive Politics 

Racial Unfairness and Fiscal Politics, with Katherine Krimmel.

Abstract: We provide and test a theory explaining how and why racial attitudes shape public opinion on government spending in the United States. We hypothesize that many people think the government allocates money unfairly across racial groups, and “inequity aversion” leads them to reject spending as a result. Using data from an original survey, we find support for our theory in the sample as a whole, and within racial, partisan, and ideological subgroups. Indeed, unfairness views are comparable to partisanship in their relationship to opinion on spending, and stronger than ideology. While prior work has shown that whites’ racial attitudes are correlated with opinion on specific government programs, we show they shape opinion about the appropriate level of government spending writ large. We also move beyond the study of white opinion, measuring views of unfairness in the distribution of spending among racial minorities as well.

Substantive Divergence: The Meaning of Public Opinion on Spending in Red and Blue, with Katherine Krimmel.

Abstract: We examine the substantive meaning of public opinion on government spending using open-ended data from an original survey. Belying the conventional wisdom on this subject, we find that public opinion on government spending is not reducible to views on social welfare programs. While most people do have specific associations with spending, in the aggregate, public associations span a wide range of government functions. Balance does not necessarily mean harmony, however. We find strong evidence of what we call substantive divergence along party lines in this area—when they think about spending, Republicans and Democrats envision different bundles of goods and services, on average. This is true even for opposing partisans with the same overall assessment of spending (e.g., those who say government spends too much). These findings bring fiscal conflict into sharper relief and also have broader implications for the conceptualization and measurement of differences across parties, as well as other political cleavages.

The Spending Paradox in Historical Perspective, with Katherine Krimmel.  

Abstract: Our paper, “The Federal Spending Paradox: Economic Self-Interest and Symbolic Racism in Contemporary Fiscal Politics,” documents a positive relationship between state-level opposition to federal spending and net federal outlays to states, a phenomenon we have termed the “spending paradox.” This relationship is interesting, since it is counter-intuitive, and important, since it produces odd mandates for many members of Congress representing poor states, and may help to explain some of the chaos afflicting contemporary fiscal politics. Adding intrigue, we suspect there is a temporal dimension to the paradox—that the puzzling correlation between opposition and outlays we observe in the wake of the Great Recession did not exist following the Great Depression. This epilogue explains why we expect to find a temporal dimension, offers preliminary evidence for its existence, and explores a few temporal comparisons to reveal some of the questions we’ll need to address in our larger project in order to explain the changing dynamics of fiscal politics over the postwar period.

How Should We Estimate State-Level Opinion on Quota-Sampled Data from the 1930s and 1940s? An Evaluation of Multilevel Regression and Poststratifi cation with Katherine Krimmel.

Abstract: This paper addresses the challenges of using historical quota-sampled polling data for state-level opinion estimation using multi-level regression and poststratification (MRP). We evaluate (1) whether MRP can produce accurate estimates of subnational opinion with early surveys; (2) which individual and group-level predictors facilitate the most accurate estimate; and (3) how much data is needed.

Party Effects on the Distribution of Federal Outlays: A Regression Discontinuity Approach with Austin Nichols. 

Abstract: Do parties affect the pattern of distributive spending in the U.S. House of Representatives? Party-cartel theories of legislative organization posit that majority party status accords party members influence over legislative outcomes that they would not otherwise wield. The implication for distributive spending is that a majority party member elected from a given district could extract more distributive benefits for the district than a could minority party member even if elected by the same district for the same Congress. We use a regression discontinuity design that exploits a particular feature of the U.S. majoritarian voting scheme—that the majority party status of the winner is “assigned” discontinuously at fifty percent (plus one vote) of the majority party vote share—to investigate the effect of being represented by majority party member on distributive spending in the district. Using data on federal spending in districts from fiscal years 1983 to 2002, we determine if federal spending as a function of the percent of the electorate that voted for the majority party candidate “jumps” at fifty percent. If there is a significant jump in spending near fifty percent, this would indicate that the majority party does indeed use its power to secure more federal funds than the minority party in marginal districts. Our design also allows to test whether Democrats or Republicans are bigger spenders in marginal districts, by exploiting the fact that the party affiliation of a district’s representative is assigned discontinuously at fifty percent (plus one vote) of the two-party vote for the Democrat. Using RD, we find no evidence of a causal effect of majority party status nor of party affiliation on outlays to the district.

Malapportionment in the U.S House of Representatives: The Effect of Census Reapportionment on the Distribution of Federal Funds to States. 


Quantitative Methods and Other Work

Randomization Tests and Inference with Grouped Data

Abstract: Political scientists often ask questions that require making inferences about the effects of variables measured at the group level on outcomes measured at the individual level. Inference with grouped data presents special challenges because the amount of independent information in the data is often more related to the number of groups than to the number of individual observations. A common parametric solution to this problem is to calculate cluster-robust standard errors and to use those errors in hypothesis tests. However, cluster-robust standard errors perform poorly when the number of groups is fewer than 50. I present Monte Carlo evidence which shows that, in terms of Type I error rates, the non-parametric randomization test outperforms t-tests using cluster-robust standard errors regardless of the number of groups. In terms of power, the loss from using randomization tests is small. Thus, randomization tests are a viable alternative to the cluster-robust approach, particularly when the number of groups is small.

Analyzing Democratic Trade: When Less is More, with Robert Erikson and Pablo Pinto

Abstract: Does being a democracy cause a nation to seek out other democracies as trade partners? Research on this question has a long history, whereby the unit of analysis is the dyad-year (e.g., Canada-Belgium, 1994). However, dyadic analysis yields conventional tests of significance that are over-confident. This paper replaces the dyad with the nation as the unit of analysis. It asks whether nations that undergo democratic (or autocratic) transformations shift their trade toward (against) democracies. With this design, we find strong statistical evidence for the democratic trade hypotheses. We suggest that many research questions where dyadic analysis is the norm can more successfully be conducted with a difference-in-differences design.

Election Laws and Voter Turnout Among the Registered: What Causes What? with Robert Erikson. 

Abstract: Scholars make causal claims about the vote-boosting power of laws designed to increase turnout, citing evidence from regression analyses that show that generous voting laws are related to high turnout. Yet one must be skeptical of contamination from endogeneity in this relationship. The skeptic’s argument is: states with a culture of participation pass legislation designed to encourage voting. With participatory states being the cause of pro-turnout legislation, the causal direction is reversed from what is normally supposed. We take the skeptic’s argument seriously and use sensitivity tests to evaluate claims that turnout is influenced by pro-turnout legislation (and vise versa). Specifically, we apply a “zero covariance restrictions” assumption and estimate the effect of turnout on legislation via two-stage least squares, with state demographic variables as instruments. Then, assuming that there are no unobserved variables that affect both turnout and legislation, we can back out the reverse effect of legislation on the vote. The 2SLS analysis shows that the turnout-legislation effect fully accounts for the turnout-legislation covariance, leaving no room for legislation to affect turnout.