Month: March 2016

More on The Divisions in House Republican Party (March 2016)

voteviewblog 114th Congress, 2016 Politics, alpha_NOMINATE, Contemporary American Politics, Political Polarization

To recap: As we discussed in earlier posts, alpha-NOMINATE is a new form of NOMINATE that is fully Bayesian and is meant to replace W-NOMINATE which is now getting close to being 34 years old (the multidimensional version, written by Nolan McCarty and Keith Poole, is over 25 years old). NOMINATE was designed by Keith Poole and Howard Rosenthal during 1982-1983. It used a random utility model with a Gaussian deterministic utility function (see pages 14 – 15 of the linked 1983 paper) and logistic error (random draws from the log of the inverse exponential). The Gaussian deterministic utility function is able to capture non-voting due to indifference and alienation.

Alpha-NOMINATE is a mixture model in which legislators’ utility functions are allowed to be a mixture of the two most commonly assumed utility functions: the quadratic function and the Gaussian function assumed by NOMINATE. The “Alpha” is a parameter estimated by Alpha-NOMINATE that varies from 0 (Quadratic Utility) to 1 (Gaussian Utility). Hence, in one dimension with Alpha = 0, Alpha-NOMINATE is identical to the popular IRT model. Thus Alpha-NOMINATE can actually test whether or not legislators’ utility functions are Quadratic or Gaussian.

Below we apply Alpha-NOMINATE to the the 114th House through mid-March 2016. There have been 834 total votes of which 718 are scalable (at least 2.5% in the minority; that is, votes that are 97-3 to 50-50). We used the R version of Alpha-NOMINATE to perform the analysis. We used 4000 samples from a slice sampler in one dimension with a burn-in of 1000. The first graph shows the Trace and Density plots for alpha.

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The mean of alpha is 0.99986 with a standard deviation of 0.00014 strongly indicating that the Representatives’ utility functions were Gaussian.

Below is a smoothed histogram of the 3000 configurations after burn-in. The divide between Democrats and Republicans is a very deep one.

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Of more interest, however, are the clear divisions in the Republican Party shown in the smoothed histogram. The gap between Speaker Ryan and the head of the Freedom Caucus Jim Jordan (R-OH) is very wide. Given the turmoil in the Republican Presidential Nominating process, it is growing harder and harder for Speaker Ryan to restore “regular order” and pass a budget. With Hillary Clinton leading both Donald Trump and Ted Cruz in the polls and the competition between Trump and Cruz to gain the 1237 delegates they need for the nomination likely to drag out until at least May and perhaps even to the convention in July, this is likely to paralyze the House Republican Party for some time. This potential paralysis has motivated one of the members of the Freedom Caucus, Paul Gosar (R-AZ), to lead an effort to stop any post-Presidential Election or “Lame Duck” session of Congress for fear that spending “deals” would be struck by the leaders of both Political Parties. Depending on the state of the Presidential race in September this issue could get entangled with Presidential campaign politics. (The House is scheduled to go into recess on September 30th.) All in all, it will not be a boring year!

The next five plots show the estimated ideal points for the 435 Members who served during the 114th through mid-March along with their 95% Credible Intervals. Furthest left is Grijalva (D-AZ) at -2.38 followed by Lee (D-CA) at -2.16. On the far right are Massie (R-KY) at 4.16, Amash (R-MI) at 4.52, and Jones (R-NC) at 5.73.

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How Would the GOP Contenders Fare in a Matchup with Hillary Clinton?

voteviewblog 2016 Politics, Contemporary American Politics

The 2016 American National Election Study (ANES) Pilot Study asked respondents who they would vote for in a series of randomized general election matchups between Hillary Clinton and a series of Republican candidates (we focus on Donald Trump, Ted Cruz, and Marco Rubio). Bernie Sanders and John Kasich were not included in these matchups.

We model respondents’ choices between Hillary Clinton and the Republican candidate across the treatments of Trump, Cruz, or Rubio as the nominee. We include party ID, ideology, education, income, gender, race, and trade attitudes as predictor variables, also estimating interaction effects between GOP candidate, party ID, and education/trade attitudes/gender in a bivariate probit model.

Below we plot the interaction effects on predicted probabilities of supporting the Republican candidate. The main finding is that Trump divides the electorate by gender, education, and trade attitudes like no other. Among independents (coded “4” on the party ID scale), for instance, there are huge gaps in predicted Trump support on each of these variables. Across party identification, women, those with college/postgrad degrees, and voters supportive of free trade agreements are much less likely to support Trump than men, those with high school degrees or less, and voters opposed to free trade agreements.

These findings, of course, are hardly surprising, although the magnitude of the effects took us aback. If Trump is the GOP nominee, his path to victory would rely on the bloc of the electorate least likely to vote. Based on weighted values from the 2016 ANES Pilot Study, only 38% of independents with a high school diploma or less said they voted in the 2012 election (which, as a self-report measure, is itself an overestimate). This is a meaningful slice of the electorate—comprising about 6% of all voters, again with weights applied—but one whose turnout has historically lagged. Hence, the real uncertainty surrounding a Trump nomination.

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NOTE: “1” indicates less than high school education, “6” indicates postgrad degree.



NOTE: “1” indicates strong opposition to free trade agreements, “7” indicates strong support.

Multidimensional Scaling of Feeling Thermometers from the 2015 CCES and 2016 ANES Pilot Study

voteviewblog 2016 Politics, Contemporary American Politics, Political Polarization

Below, we use a multidimensional scaling method (metric unfolding) to analyze feeling thermometers data from two recent national public opinion surveys: the 2015 Cooperative Congressional Election Study (CCES) and the 2016 American National Election Study (ANES) Pilot Study. Both surveys asked respondents to rate their feelings towards candidates and groups (for example, Donald Trump, Hillary Clinton, and Muslims) on a 100 point scale. We transform the thermometer ratings into distances and produce a spatial map of the results, much as we would to produce a map of cities from on a spreadsheet of driving distances between the cities.

The results are shown below, with the survey respondents marked as “D”, “R”, and “I” based on their party identification. In both plots, the first dimension (the horizontal axis) represents the familiar partisan-ideological divide, separating liberal/Democratic groups and candidates from conservative/Republican groups and candidates. Groups like scientists and college professors are placed in the center-left, while groups like the police are placed center-right.

We suspect that the second dimension is tapping into establishment vs. outsider divisions in both parties: between Hillary Clinton and Bernie Sanders among Democrats, and between Donald Trump and the other candidates (particularly Jeb Bush) among Republicans. Trump is preferred by the larger cluster of Republican voters in the top-right quadrant of both plots, while Bush is preferred by the smaller clusters of Republicans in the bottom-right quadrants. Cruz and Rubio are both somewhere in between.

Within the parties, respondents’ relative preferences between the candidates do not appear to follow a traditional liberal-conservative divide, but are structured along a separate dimension—perhaps involving establishment vs. outsider attitudes and preferences on cross-cutting issues like free trade.

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The Heroin Epidemic

voteviewblog 114th Congress, Contemporary American Politics

This past Wednesday, 2 March 2016, there was a procedural vote in the Senate to waive budget caps in order to appropriate more funds to fight the epidemic of Heroin and other Opioids (just search Google News for countless recent articles across the country on this). Sam Quinones in his book Dreamland details the origins of the recent epidemic in the widespread use of Oxycodone (OxyContin is the time released form of Oxycodone) and Black Tar Heroin from Mexico. The Opioid epidemic became an issue in the recent New Hampshire Primary but it is a nationwide problem. Atlanta’s Channel 11 television news just did a four part series on how widespread Heroin is in Atlanta’s affluent northern suburbs where packages of heroin are delivered to the front doors of users (the user leaves money under a doormat and the deliveryman takes the money and leaves the heroin).

Below we show the procedural vote on more funds to fight the Opioid epidemic using our Constant-Space DW-NOMINATE Scores. Five Republicans voted “Yea” — Ayotte (R-NH), Collins (R-ME), Graham (R-SC), Kirk (R-IL), and Portman (R-OH). The cutting line goes through the lower left portion of the Republican Party and there are only four “errors” on the roll call with a PRE of 0.91.

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Portman’s vote for addition funding is significant. Quinones starts his investigation of the twin epidemics in Portsmouth, Ohio, on the Ohio river. Southern Ohio has been hit hard by the Opioid epidemic and Governor Kasich expanded Medicaid under the ACA in part because of the impact of Oxycodone and Heroin in Ohio. His argument is that treatment and helping the addicted to regain their independence and hold jobs is better than incarceration. Hopefully his point of view will prevail.