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For those of you coming from the Monkey Cage: welcome!

This is a blog on my research and other topics of interest. I'm in the middle of a series on incorrect survey weighting, which is part of a larger series on reproduction in social science. I'm a proponent of research transparency, such as preregistration of experimental studies to reduce researcher degrees of freedom, third-party data collection to reduce fraud, and public online archiving of data and code to increase the likelihood that error is discovered.

My main research areas right now are race, law, and their intersection. I plan to blog on those and other topics: I am expecting to post on list experiments, abortion attitudes, the file drawer problem, Supreme Court nominations, and curiosities in the archives at the Time-Sharing Experiments for the Social Sciences. I hope that you find something of interest.

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UPDATE (May 21, 2014)

Links to the Monkey Cage post have been made at SCOTUSBlog, Jonathan Bernstein, and the American Constitution Society.

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UPDATE (May 21, 2014)

Jonathan Bernstein commented on my Monkey Cage guest post, expressing skepticism about a real distinction between delayed and hastened retirements. The first part of my response was as follows:

Hi Jonathan,

Let me expand on the distinction between delayed and hastened retirements.

Imagine that Clarence Thomas reveals that he wants to retire this summer, but conservatives pressure him to delay his retirement until a Republican is elected president. Compare that to liberals pressuring Ruth Bader Ginsburg to retire before the 2016 election.

Note the distinctions: liberals are trying to change Ginsburg's mind about *whether* to retire, and conservatives are trying to change Thomas's mind about *when* to retire; moreover, conservatives are asking Thomas to sacrifice *extra* *personal* time that he would have had in retirement, and liberals are asking Ginsburg to sacrifice *all* the rest of her years as *one of the most powerful persons in the United States.*

Orin Kerr of the Volokh Conspiracy also commented on the post, at the Monkey Cage itself, asking why a model is necessary when the sample of justices is small enough to ask justices or use past interviews. My response:

Hi Orin,

Artemus Ward has a valuable book, Deciding to Leave, that offers more richness than statistical models offer for investigating the often idiosyncratic reasons for Supreme Court retirements. But for addressing whether justices retire strategically and, if so, when and under what conditions -- or for making quantitative predictions about whether a particular justice might retire at a given time -- there is complementary value in a statistical model.

1. For one thing, there is sometimes reason to be skeptical of the reasons that political actors provide for their behavior: there is a line of research suggesting that personal policy preferences inform Supreme Court justice voting on cases, though many justices might not admit this in direct questioning. Regarding retirements, many justices have been forthcoming about their strategic retirement planning, but some justices have downplayed or denied strategic planning: for example, Ward described press skepticism of Potter Stewart's assertion that he did not strategically delay retirement while Jimmy Carter was president (p. 194).

Statistical models permit us to test theories based on what Stewart and other justices *did* instead of what Stewart and other justices *said*, similar to the way that prosecutors might develop a theory of the crime based on forensic evidence instead of suspect statements.

2. But even if the justices were always honest and public about their reasons for retiring or not retiring, it is still necessary to apply some sort of statistical analysis to address our questions. By my count, from 1962 to 2010, 5 justices retired consistent with a delay strategy and 8 justices retired when the political environment was unfavorable. Observers using simple statistical tools might consider this evidence that justices are more likely to retire unstrategically than to delay retirement, but this overlooks the fact that justices have more opportunities to retire unstrategically than to delay retirement.

For example, assuming that no conservative retires during President Obama's eight years in office, the five conservative justices as a group will each have had eight years to retire unstrategically, for a total of 40 opportunities; but liberal justices have had fewer opportunities to delay retirement: Breyer, Ginsburg, Souter, and Stevens each had one opportunity to retire consistent with a delay strategy in 2009, and -- presuming that justices stay on another year to avoid a double summer vacancy -- Breyer, Ginsburg, Sotomayor, and Stevens each had one opportunity to retire consistent with a delay strategy in 2010, for a total of 8 opportunities.

In this particular period, the proper comparison is not 2 delayed retirements to 0 unstrategic retirements, but instead is 2 delayed retirements out of 8 opportunities (25%) to 0 unstrategic retirements out of 40 opportunities (0%).

3. Sotomayor's addition in the 2010 data highlights another value of statistical models: they permit us to control for other retirement pressures. Statistical models can help account -- in a way that qualitative studies or direct questioning cannot -- for the fact that the 2010 observation of Sotomayor is not equivalent to the 2010 observation of Ginsburg because these justices have different characteristics on other key variables, such as age. From 1962 to 2010, justices retired 14 percent of the time during delayed retirement opportunities, but retired only 4 percent of the time during unfavorable political environments. But these percentages should not be directly compared because there might be spurious correlations that have inflated or deflated the percentages: for example, perhaps older and infirm justices were more likely to experience a delayed opportunity and *that* is why the delayed percentage is relatively higher than the unstrategic percentage. Statistical models let us adjust summary statistics to address such spurious correlations.

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Bill James is said to have said something to the effect that bad statistics are the alternative to good statistics. Relying only on justice statements instead of good statistics can introduce inferential error about justice retirement strategies in the aggregate in several ways: (1) justices might misrepresent their motives for retiring or not retiring; (2) we might not properly account for the fact that justices face more unstrategic opportunities than delayed opportunities or hasten opportunities; and (3) we might not properly account for variables such as age and illness that also influence decisions to retire.

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In the event of a US Supreme Court vacancy, would it be more difficult for President Obama to replace moderate conservative Anthony Kennedy or the more extreme conservative Antonin Scalia? Presuming that the president would nominate a solid liberal, it might seem that replacing Scalia would be more difficult, because replacing Scalia would cause a more leftward shift in the seat than replacing Kennedy would.

But my research here suggests that the president would receive less resistance from the Senate for a liberal-for-Scalia change. Here's why: the key senator required for confirmation is one of the more moderate senators -- the 51st senator for the confirmation vote, and the 60th senator for a cloture vote in case of a filibuster -- and the liberal-for-Scalia change is more attractive to these senators. Consider the figure below that presents the Bailey ideological ideal points of the nine Supreme Court justices in 2008 (in black) along with the ideal points of the Senate medians in 2006 and 2008.

BaileyIdealPoints2008

The empirical evidence in the article suggests that senator opposition to Supreme Court nominees is a function of whether the change makes the senator better off ideologically in terms of the senator's ideology being reflected on the Court. Conservative senators are likely to oppose the nomination of a liberal in either case because both the liberal-for-Kennedy change and the liberal-for-Scalia change move the ideology of the seat away from conservative senators; liberal senators are likely to support the nomination of a liberal in either case because both the liberal-for-Kennedy change and the liberal-for-Scalia change would move the ideology of the vacant seat toward liberal senators; but there's a difference for moderate senators: the liberal-for-Kennedy change would move the ideology of the vacant seat away from the moderate senators close to Kennedy, but the liberal-for-Scalia change would not change for moderates, because neither Scalia nor the liberal nominee are close to the Senate median.

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David Karol at Monkey Cage discusses the Supreme Court:

The broader point is that the whims of one unaccountable person, whatever their age, abilities or ideology should NOT matter so much in a democracy.

Karol proposes eighteen-year terms, which reduce the length of time that the "whims of one unaccountable person" matter but do not reduce the relative importance of that person's whims on any given case or in any given year. But court expansion would reduce the "cross-sectional" power of a justice and thus reduce the associated concern for the health of like-minded justices, severely curtailing the chance of a judicial Weekend at Bernie's.

Of course, it is not politically feasible to give any president multiple new nominations, but it is possible to expand the Court to eighteen members without packing and with minimal disruption to the status quo:

  1. Give each current justice two votes and each new justice one vote: when a current justice vacates a seat, the president and the Senate replace the current justice with two new justices; when a new justice vacates a seat, the president and the Senate replace the new justice with one new justice.
  2. Let's say that we want an eighteen-member Court immediately. Let each sitting justice nominate one new justice. The sitting justices would have a strong incentive to nominate a candidate with similar judicial and ideological views.

Eighteen-member or eighteen-vote Courts would have a greater potential for tie votes, but this is less a problem than a feature with positive consequences, since a majority of the full Court is now a 10-to-8 supermajority, which makes it slightly more difficult for the Court to overrule a lower court or alter its own precedent.

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High LSAT scores in a given major have been used to recruit students into philosophy and physics. But high LSAT scores do not necessarily reflect the ability of a major to prepare students for the LSAT or for the legal profession, because students self-select into majors: high school students with an interest in philosophy or physics might already possess the verbal and analytical skills that the LSAT tests, so that high LSAT scores for philosophy or physics majors might reflect only the pre-existing abilities of students who select those majors.

The graph below illustrates this possibility with a plot of 2007 LSAT scores grouped by major against 2003 SAT scores grouped by intended major. Some majors have been combined* and control variables were not included in the analysis**, so the graph should be interepreted with caution: but the general pattern is a relatively high correlation between SAT scores and LSAT scores (r=0.89, n=16, p<0.01).

LSAT2007SAT2003

Sources: 2007 LSAT data from Nieswiadomy (2009), and 2003 SAT scores from the College Board.

* Accounting, Business Management, Business Administration, Finance, and Marketing majors were grouped into the Business intended major; Interdisciplinary Studies and Liberal Arts majors were grouped into the General Studies intended major; Chemistry and Physics/Math majors were grouped into the Physical Sciences intended major; Criminal Justice, Government/Service, and Pre-Law majors were grouped into the Public Services intended major; and Anthropology/Geography, Economics, History, International Relations, Political Science, Psychology, and Sociology/Social Work majors were grouped into the Social Sciences intended major.

** For example, the analysis does not account for students who drop out or students who switch majors; the analysis considers data for only the set of students who took the SAT in 2003 and the separate but presumably overlapping set of students who took the LSAT in 2007; the analysis also does not account for selection bias with regard to students sitting for the LSAT: for instance, mathematics majors who take the LSAT might be less intelligent or more intelligent than the average mathematics major.

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