by geezer in Paris
Wed Jun 24th, 2009 at 03:49:46 AM EST
Nate Silver of fivethirtyeight.com has done a great job of doing a quick-and-dirty model to prove what we all knew all along- that money buys policy. So why am I excited? Because I'm one of those odd people who question my own certainties-- who likes to find that, once in a while, I was certainly wrong.
Not this time.
"As I lamented yesterday, health care is one of those areas where both popular opinion and sound public policy seem to take a backseat to protecting those stakeholders who benefit from the status quo. But can we actually see -- statistically -- the impact of lobbying by the insurance industry on the prospects for health care reform? I believe that the answer is yes."
"I decided to build a model to explain and predict whether a particular senator supports the public option. The variables in the model are as follows:
-- The senator's ideology, as measured by his DW-NOMINATE score;
-- Per capita health care spending in the senator's home state;
-- Lobbying contributions received by the senator from health insurance PACs since 2004.
Below the jump, I explain each of these in a bit more detail.
Ideology. DW-NOMINATE scores measure a senator's ideology on a scale that generally runs from -1 (extremely liberal) to +1 (extremely conservative), although scores slightly less than -1 or slightly greater than +1 are possible under unusual circumstances. These days, the average Democratic senator has a score of -.44, and the average Republican senator a score of +.48.
DW-NOMINATE data has not yet been published for the 111th (current) Congress, so I use data from the 110th Congress instead. For freshman senators, I extrapolate DW-NOMINATE scores by translating (via regression analysis) Progressive Punch scores. Extrapolated scores for freshmen members of the Senate are as follows:
Udall, T -.472
Udall, M -.420
In addition, a special score is required for Arlen Specter, who recently switched parties. Specter's score is extrapolated based on a recent analysis we did of his voting behavior since becoming a Democrat. Specter's score according to this analysis is -.255. This makes Specter the fifth most conservative Democrat, slightly to the left of Evan Bayh and slightly to the right of Tom Carper.
Per Capita Health Care Spending. As estimated by the Department of Health and Human Services. We use data from 2004, which is the most recent available. Health care spending varied in 2004 from $3,972 per head in Utah to $6,683 per head in Massachusetts.
PAC Contributions. Based on data downloaded from OpenSecrets.org, a.k.a. the Center for Responsive Politics. Contributions were tallied from two industry codes: F3200 (Accident & Health Insurance) and H3700 (HMO's). Data covers the 2004, 2006 and 2008 and 2010 campaign cycles. The fundraising data is adjusted based on the number of cycles that the senator has participated in as a Congressman (including time spent in the House of Representatives) or as a candidate, where 2010 is treated as 1/8th of a cycle since one quarterly report has so far been filed from the two-year period. So, for example, a senator that ran for and won office in 2006 is treated as participating in 2 1/8th out of a possible 3 1/8th cycles: 2006 as a candidate, and then 2008 and the fractional cycle in 2010 as a senator."
In fairness, I'll quote somewhat sparingly,- there's lots- because Nate's work should be read in it's entirety. Link above.
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Here's a teaser for those who are short of reading time:
The model employed is a standard logistic regression with these three variables: ideology, lobbying and health care costs. Ideology is statistically significant at the 99th percent level, PAC contributions at the 95th percent level, and health care costs -- senators in states with more health care spending are more likely to support the public option -- at the 90th percent level. The R-squared for the model is .61, which means that these three variables alone give us 61 percent of the information that we need to predict a senator's position on the public option. The model guessed the senator's position correctly in 87 out of 99 instances.
There are several neat things we can do with this.
One is to evaluate the impact of insurance industry money on a senator's likelihood of supporting the public option, holding ideology and health care spending in the senator's home state constant. The chart below presents these estimates for a liberal (DW-NOMINATE score of -.6), mainline (-.4) and centrist (-.2) Democrat, as well as for a centrist (+.2) Republican:
Lobbying contributions appear to have the largest marginal impact on middle-of-the-road Democrats. Liberal Democrats are likely to hold firm to the public option unless they receive a lot of remuneration from health care PACs. Conservative Democrats may not support the public option in the first place for ideological reasons, although money can certainly push them more firmly against it. But the impact on mainline Democrats appears to be quite large: if a mainline Democrat has received $60,000 from insurance PACs over the past six years, his likelihood of supporting the public option is cut roughly in half from 80 percent to 40 percent.
But does it hold water? James Kwak at Baseline scenario thinks it does pretty well.
Modelling everything, Public Plan edition
Mark Nyhan has a counterargument, and cites the usual raft of papers--
"Nyhan says "studies have typically found minimal effects of campaign contributions on roll call votes in Congress," and cites a Journal of Economic Perspectives paper as backup."
So Kwak looked it over. His conclusions follow:
"OK, Nyhan may be right. But he may not be.
I looked at that paper. First, it cites a stack of papers that support Silver's view (that campaign contributions do influence policy). (Of course, it's common to cite the papers you are trying to refute.) Then it describes a logical argument against Silver's view ("Tullock's Puzzle"), which makes no sense to me, at least as summarized there. The argument is that campaign contributions are pitifully small given the amounts of money at stake, and so firms cannot possibly see contributions as an investment in policy. For example:
Dairy producers, who since 1996 have had to have subsidies renewed annually, gave $1.3 million in 2000 and received price supports worth almost $1 billion in the Farm Security and Rural Investment Act of 2002.
I dont' see the puzzle; if I can get $1 billion in subsidies by paying $1.3 million, why would I pay any more? It seems to me that the explanation here has to do with special-interest politics; no other constituency is sufficiently mobilized to fight against dairy producers, so they get their subsidy. Here's the conceptual argument: "The figures above imply astronomically high rates of return on investments. In a normal market, with such high rates of return, existing donors should want to increase their contributions." But this assumes that the "investment return" on campaign contributions is a smooth, monotonic (always increasing) function, which seems fundamentally at odds with the way Congress works. But as I said, maybe Tullock did a better job explaining his puzzle.
Finally, they do a regression of "roll call" votes in Congress against campaign contributions and find little influence. But this analysis has serious limitations in the present context.
First, the dependent variable is the aggregate rating of each legislator by the U.S. Chamber of Commerce. (They got similar results using other organizations.) That is, it's an average of a large number of votes made in the course of a session on a large number of issues. So the finding is that corporate contributions only pull a legislator a couple of points toward the Chamber of Commerce's positions overall; but that doesn't mean that on a given issue, he might switch his vote because of one or two large campaign contributors from the affected industry.
Second, it ignores the complexities of the legislative process. On many key issues, there is no roll call. For example, whether the public plan even comes to a meaningful vote will depend on Harry Reid - who may not even want the public plan - and whether he thinks he has the votes. The power of some members of Congress goes well beyond their individual votes.
Third, the data are from 1978-1994. I'm not a student of American politics, but casually reading The New York Times indicates a few changes in politics since 1994: there is more money; there is more money that is not controlled by political parties (weakening bonds to party, which historically explained a lot of votes); and there is more money that gets spent directly on advertising and is not contributed to political campaigns. This last factor could cut either way, but I think it's fair to assume that if a company gave you $50,000, they are probably also donating to soft-money groups that take the same positions.
So here we have: on the one hand, a quick-and-dirty model on this specific question by a guy without a Ph.D. in anything (I think), which correctly picks the positions of 87 out of 99 senators (but it's possible that the model would have done just as well without campaign contributions); on the other hand, a guy with a Ph.D. in political science and a research fellowship in health policy at a very good university, citing a paper by three MIT professors that's more or less on the same general topic, arguing that campaign contributions don't affect policy.
I'd like to refer the reader to my diary, The best and the Brightest
, for some thoughts and good links as to why the pedigree James quotes may mean something very different than would appear.
I respect Kwak's efforts to place the work in context, but I think it's value is apparent As do the readers at Baseline, as shown by the comments.
Seems there's real predictive value here, too. How nice:
What happens if we set the lobbying variable to zero for all senators? That is, suppose that the health care insurance industry were prohibited from making political contributions? In that case, the model predicts, 47 senators would currently support the public option, as opposed to the 38 who actually do. In other words, the insurance industry's influence appears to swing about 9 votes against the public option. Whatever number of senators wind up supporting the public option, add 9 to it, and you'll have a decent ballpark estimate for what the level of support might be if not for insurance industry contributions.
The relationship Nate Silver explores between money and policy is a crucial one, in all quasi-democratic, Western-style political settings, and Nate's work has obvious value in Europe as well as in the US, as at least a good starting point to try to get a handle on it in a comprehensible way.