Competing Agendas in Theories of Congress
Assessing Agenda Control Using Counterfactual Data
Bibliographic Data
| ID | 6385138 |
|---|---|
| Authors | Gregory Robinson (Binghamton University, corresponding author) |
| Year | 2015 |
| Volume | 77 |
| Issue | 3 |
| Pages | 749-761 |
| Publication date | 2015-07-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Journal of Politics (JOURNAL) |
| Journal identifiers | ISSN: 0022-3816 • E-ISSN: 1468-2508 |
| Publisher | University of Chicago Press (PUBLISHER • US) |
| DOI | 10.1086/681589 |
| OpenAlex | W2053223599 |
| Language | EN |
| Citations received | 3 |
| References cited | 22 |
In legislative studies, a “roll rate” refers to the proportion of votes where a member or group of members is “rolled”—voting no on a measure that passes. Roll rates analysis is a potentially useful tool for evaluating arguments that the majority party in the House exercises influence by controlling what does and does not make it onto the agenda. Despite its promise, so far the use of roll rates to test these arguments has faced the problem of observational equivalence—that the predictions of partisan theories of agenda control are indistinguishable from those of arguments that have no place for parties. I address this problem by calculating party-less and partisan counterfactual roll rates data to pin down the predictions of these theories. This offers a powerful research design to evaluate observed roll rates from sample Congresses. The results provide intriguing evidence for partisan theories of the House agenda
Control (management · Counterfactual thinking · Economics · Equivalence (formal languages · Law and economics · Legislature · Measure (data warehouse · Observational study · Political science · Politics · Positive economics · Public economics · Sample (material · Test (biology · Voting · Computer Science · Electoral Systems and Political Participation · Fiscal Policies and Political Economy · Law · Mathematics · Policy Transfer and Learning · Psychology · Public Administration · Social Psychology
Parties and Leaders in the Postreform House
Information and Legislative Organization
The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant
An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
Beyond the Median
On Measuring Partisanship in Roll-Call Voting
Buying Negative Agenda Control in the U.S. House
Estimating Proposal and Status Quo Locations Using Voting and Cosponsorship Data
Do Restrictive Rules Produce Nonmedian Outcomes? A Theory with Evidence from the 101st−108th Congresses
Representation in Congress
Unpacking Agenda Control in Congress
Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation
Multidimensional Analysis of Roll Call Data via Bayesian Simulation
The Macropolitics of Congress
Who Wins? Party Effects in Legislative Voting
Where's the Party
Parties, Pivots, and Policy
The Statistical Analysis of Roll Call Data
| Citations per year | 0.5 |
|---|---|
| Citation span | 2020 - 2022 (3) |
| Highly cited | No |