Following on Andrew’s post, here’s a graph from political scientist Tobin Grant:
The current Congress and the next least productive Congresses are highlighted.
The 112th Congress has not yet ceased to be, but as of today the Library of Congress’s “Thomas” site shows that 173 bills have become public law since January 2011. Legislators should add at least one more this week, albeit with the continuing resolution punting the fiscal 2013 budget sometime into calendar year 2013 (thus passing on any given session’s most important obligation.) The lame duck session after the election will add to the total as well. Even so, as Jennifer Steinhauer pointed out yesterday, the present Congress has done far less than the so-called “Do Nothing” 80th Congress of 1947-48, which produced 906 laws.
The average number of enactments in a given Congress from 1947 through 2010 (via quick calculations from the Resume of Congressional Activity) is 637. And if the do-nothing Congress actually did quite a lot, the 112th Congress will fall well short even of the current record holder for fewest enactments in the postwar period, the 104th Congress of 1995-96. That Congress produced 333 laws.
For many, of course, the less Congress does, the better. And we should be cautious of equating activity with productivity generally. Still, if anything, the 112th Congress’s figure is too high. After all, more than 20%—thirty-seven(! )—of the laws passed thus far in 2011-12 are acts re-naming post offices, courthouses, plazas, and wilderness areas. (A 38th tells the Treasury to mint commemorative coins to help fund the National Baseball Hall of Fame. Motherhood and apple pie coins did not survive Senate filibuster.)
Jeffrey Frankel, a distinguished economist, public servant, and expert on international trade, made a common but, I hope, avoidable statistical error in a recent column. Frankel wrote:
Compared to “blue-staters,” those who live in red states exhibit less responsibility, on average, in their personal behavior: they are less physically fit, less careful in their sexual behavior, more prone to inflict harm on themselves and others through smoking and drinking, and more likely to receive federal subsidies . . . Blue-state residents, who tend to be more educated and have higher incomes than residents of red states . . .
This is all fine, but Frankel is making a common, and important, mistake, which one might call “personifying the states.” In fact, as we describe in detail in our book Red State Blue State, differences between state averages do not necessarily reflect individual differences. For example, blue state residents have higher incomes, on average, than red state residents; but Democratic (“blue”) voters are poorer, on average, than Republican (“red”) voters. Even Mitt Romney knows that!
Similarly, it is misleading to write, “Statistical analysis shows that states where more residents suffer from obesity, often because they get less physical exercise and eat more junk food, tend to vote Republican. To illustrate, a mere 1% decrease in a state’s obesity on average is estimated to raise the ratio of Democratic to Republican voters from 1.00 to 1.07”—an argument that conflates individuals and states and confuses correlation with causation.
Frankel’s mistake is an easy one to make; others who have confused state-level with aggregate patterns include respected commentators Nicholas Kristof, Michael Barone, and Tucker Carlson. Seeing this mistake made by a leading scholar and former member of the Council of Economic Advisors has motivated me to post on this topic once again.
P.S. See here for the sugar-subsidy story.
The following is a guest post by political scientist Keith Darden (Yale University) and Harris Mylonas (George Washington University). Please note that the symposium in Ethnopolitics that they refer to in their article has generously been ungated and made available to all for free for a limited time in conjunction with this post.
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The killing of the US Ambassador last week in Benghazi and the recent wave of attacks on NATO personnel by uniformed Afghan police and military highlight the perils of international efforts to build states and societies on foreign soil. Why is it that the people we arm and assist keep on turning those weapons against us?
The New York Times, CBSnews, Washington Post, all reported on Sept 17, 2012 that the number of NATO personnel killed in Afghanistan by uniformed Afghan military and police is already at 51 this year, up from a total of 35 for all of last year. Approximately one in six of the NATO soldiers killed in Afghanistan this year were killed by our local allies and trainees. And this only counts those who killed while in uniform. The attrition and desertion rate from the Afghan National Army and police forces is exceptionally high and many have joined the ranks of the Taliban. If we consider the number of allied personnel killed by soldiers and police who have been armed and trained by coalition forces, the number is certainly much higher.
The US has wisely put the training of the Afghan Local Police (ALP) on hold for a month until it can improve procedures for vetting its recruits, but the problem runs much deeper.
In a symposium published recently in Ethnopolitics we debated the merits of international state-building efforts. Our main lesson: There is more to state-building than simply expanding the ranks of the army and police. Expanding the army and police may be state-building, but it might just as easily be insurgency-building if it is not preceded by systematic efforts to build loyalty and to carefully select recruits. If you are unsure of the loyalties of the recruits who you are training, it’s best not to train them at all.
Here is the link to our piece, which was followed by some responses (Erin Jenne, Fotini Christia, Gordon Bardos, David Siroky & Yoav Gortzak) and our reply to their thoughtful comments.
John, Ben Highton, and I predicted that Democrats will get roughly half the vote but only about 45% of the seats. To what extent is this a product of the redistricting? If not for the redistricting, would Democrats be doing better?
We approach this question by asking what our model would predict using the old districts, as well as the incumbents sitting in those districts at the beginning of 2012. In other words, assume that the current crop of candidates was running but the 2011 redistricting had never happened. Comparing our original prediction to this counterfactual incorporates both forms of partisan redistricting effects: new district lines and the “displacement” effects of some incumbents forced to retire or run in uncomfortable territory.
Given these assumptions, our median seat prediction using the new districts was 194 Democratic seats, and the median prediction assuming the redistricting never happened is…194 seats. That’s it. The redistricting has no impact on our predicted seat share.
There are certainly reasons to have expected a different outcome. Republicans took control of the redistricting process in a number of states as a result of the 2010 election. The initial assumption seemed to be that Republicans would use this control to expand their majority (see here, here, or here). Yet since Republicans now hold more seats than in any Congress but one since before the Great Depression, it probably makes more sense to think they would protect the gains they have already made (see here and here for concurring views). That in turn would suggest the Republican seat share would remain the same even as support for Democrats grew—exactly what we’re showing.
But the changes to the districts, on balance, have been pretty small. The graph below has the distribution of the 2008 presidential vote in the 435 House districts in 2008 and 2012. (We once again rely on the Daily Kos presidential vote numbers for the new districts.) “Strong” districts have a presidential vote more than 10 points off the national average, “Lean” is between 5 and 10 points off the average, and “Tossup” is within 5 points. There is not a lot of change here: the number of seats in each category is roughly the same before and after the redistricting.
If there is a factor that explains the gap between vote share and seat share, it is more likely to be incumbency than redistricting. Congressional elections are not written on a clean slate. Instead, a substantial number of voters give their incumbent the benefit of the doubt unless offered ample reason to do otherwise. That means the party with more incumbents is going to do better, especially in a status quo election with no signs of a broader partisan tide.
There are a whole lot more Republican incumbents now than there were two years ago. That gives the party an important advantage that helps them keep seats they might otherwise lose. How important? If we take the new redistricting as given but pretend that no incumbents ran for reelection (an admittedly unrealistic scenario), our model predicts a Democratic vote share of 52% and a seat share of 51%, with a 55% chance that Democrats will take back the House. The legacy of past elections matters.
All appropriate caveats still apply. The uncertainty around the new districts is large, we haven’t taken into account any local campaign dynamics, etc. However, future campaign dynamics are unknown when the districts are drawn, so expectations are built on the factors we have already considered: the partisanship of each district and which incumbents, if any, are running for that seat. Those factors suggest the redistricting has had little net impact.
Brad DeLong writes:
There is a huge amount of mean reversion in Nate Silver’s model right now . . . Considering that Silver’s forecast F is roughly F = λ(polls) + (1-λ)(fundamentals), either λ must be really small or truly extraordinary things have happened to Silver’s fundamentals in the past week.
I don’t know what Nate’s model is, but if he’s doing things right, then indeed the weight attached to the recent week of polls must be really small. Each week’s polls provide very very little information about the election outcome, given what we already know.
For more background, see this article (with Noah Kaplan and David Park) on the random walk and mean reversion models and this article (with Kari Lock) on Bayesian combination of state polls and election forecasts.
On Monday we offered an estimate based on the fundamentals of House elections that predicted Democrats would pick up only one additional seat, with a 1 in 4 chance of regaining the majority in that chamber. How certain is this estimate? And what does that tell us about the value of this whole enterprise?
The first question is easy enough to answer. The standard error for the vote share estimate is 5.6%; for seat share, 8.7%. That’s a lot of uncertainty. It means there is at least a little probability of some pretty crazy outcomes. It explains why there is still a 1 in 4 chance that the Democrats will get the 25 seats they need to retake the House, when our own median prediction is only one seat.
The uncertainty is especially large because we don’t know exactly what the districts are like post-redistricting. Under the old redistricting plans in each state, some districts were consistently more competitive than others, beyond what the presidential vote in the district would already imply. There are a lot of reasons why that might be true. Perhaps the incumbent in that seat was particularly vulnerable, or faced a tough challenge year after year. Perhaps the seat contained a lot of wishy-washy partisans. Whatever the reason, even though we can’t explain the difference, we know roughly how large it was. Thus, any prediction involving those districts can include that extra information.
When it comes to the new districts, we don’t have that information. All we know is how the voters in each district voted in the 2008 presidential election. As a result, we’re forced to push the remaining uncertainty into our estimates, and the range of possible outcomes increases accordingly. If we pretended instead that the old districts were being used, the standard error of our seat prediction would be a lean and mean 1.9%, rather than the 8.7% we currently have.
The size of our error might reflect the economy of our model. We wanted to see how far the fundamentals could get us in House elections, and the answer may be, “pretty far, but not as far as we might like.” As I said in the original post, including things like spending or handicapper predictions might reduce the otherwise unexplained differences between districts and make us more certain. Or it may be we’re as close as we can get, and more intangible factors need to take over from here.
Regardless, I would argue that this is exactly the point of such a model. It takes some very important factors that people talk about a lot with respect to House elections, and it says both how important each one seems to be and how confident we can be about using that information to make forecasts. We can expand the model and play with different possibilities, and every result tells us something about the dynamics of House elections and what they mean for this particular year. That makes it easier to have a conversation about what matters, how much, and even why.
We are delighted to welcome the following guest post by Jessica Weiss, an assistant professor at Yale University who has extensively researched anti-Japan demonstrations in China.
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Anti-Japanese demonstrations have been reported in as many as 120 cities across China, following more than a month of escalating demonstrations against Japan’s nationalization of uninhabited islands in the East China Sea. Protests over the weekend turned violent in several cities, destroying Japanese-branded stores and cars. Although the protests have not been as deadly as some in the Middle East, the degree of property damage and vitriol—including some slogans calling for Japan’s extermination—has aroused alarm. With increased patrols by Japanese and Chinese ships and reports of a thousand-strong Chinese “fishing armada” enroute to the disputed waters, risk of military conflict between these two powers is growing. On his trip to Asia, Defense Secretary Panetta stated that “Obviously we are concerned by the demonstrations, and we are concerned by the conflict that is taking place over the Senkaku Islands.”
What significance do these nationalist protests have for China’s foreign policy? Should we dismiss these protests as mere street theater, a pressure valve, or a convenient distraction from domestic grievances? China scholars have debated the extent to which popular nationalism is a state-led strategy to bolster its legitimacy or a grassroots phenomenon that could jeopardize state control. Both views are partially correct. Nationalist protests are indeed dangerous to domestic and diplomatic stability, especially in authoritarian regimes that lack other channels for popular participation. But the government is strategic in whether it allows nationalist protesters to mobilize, weighing the diplomatic and domestic benefits of tolerance versus repression. In my forthcoming article in International Organization, I argue that it is the risk and cost of suppression that makes nationalist protest a credible diplomatic signal, giving authoritarian leaders like China’s the ability to showcase their vulnerability to mass opinion and domestic audiences.
After an extended break for his best word tournament, we once again bring you official Monkey Cage cartoonist Ted McCagg:
- New survey of small business owners: visualization, paper. It finds a narrow lead for Obama as the candidate “who is more supportive of small business.”
- Excellent look at polarization by Marc Hetherington and Jonathan Haidt. See also this new article by Shanto Iyengar, Gaurav Sood and Yphtach Lelkes.
- Josh’s thoughts on Romney 47% comments.
- Steven Sanders on the prospects for same-sex marriage, including some discussion of political science research.
- The last installment of the Lewis-Beck and Tien presidential election forecast. Their two models predict different results.
- New section on class and inequality is part of the annual Midwest Political Science Association conference. Via Nick Carnes.
