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Incentives Matter (Congress and Wall Street edition)

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Thomas Ferguson sends along this paper. From the summary:

Social scientists have traditionally struggled to identify clear links between political spending and congressional voting, and many journalists have embraced their skepticism. A giant stumbling block has been the challenge of measuring the labyrinthine ways money flows from investors, firms, and industries to particular candidates. Ferguson, Jorgensen, and Chen directly tackle that classic problem in this paper. Constructing new data sets that capture much larger swaths of political spending, they show direct links between political contributions to individual members of Congress and key floor votes . . .

They show that prior studies have missed important streams of political money, and, more importantly, they show in detail how past studies have underestimated the flow of political money into Congress. The authors employ a data set that attempts to bring together all forms of campaign contributions from any source— contributions to candidate campaign committees, party committees, 527s or “independent expenditures,” SuperPACs, etc., and aggregate them by final sources in a unified, systematic way. To test the influence of money on financial regulation votes, they analyze the U.S. House of Representatives voting on measures to weaken the Dodd-Frank financial reform bill. Taking care to control as many factors as possible that could influence floor votes, they focus most of their attention on representatives who originally voted in favor of the bill and subsequently to dismantle key provisions of it. Because these are the same representatives, belonging to the same political party, in substantially the same districts, many factors normally advanced to explain vote shifts are ruled out from the start. . . .

The authors test five votes from 2013 to 2015, finding the link between campaign contributions from the financial sector and switching to a pro-bank vote to be direct and substantial. The results indicate that for every $100,000 that Democratic representatives received from finance, the odds they would break with their party’s majority support for the Dodd-Frank legislation increased by 13.9 percent. Democratic representatives who voted in favor of finance often received $200,000–$300,000 from that sector, which raised the odds of switching by 25–40 percent. The authors also test whether representatives who left the House at the end of 2014 behaved differently. They find that these individuals were much more likely to break with their party and side with the banks. . . .

I had a quick question: how do you deal with the correlation/causation issue? The idea that Wall St is giving money to politicians who would already support them? That too is a big deal, of course, but it’s not quite the story Ferguson et al. are telling in the paper.

Ferguson responded:

We actually considered that at some length. That’s why we organized the main discussion on Wall Street and Dodd-Frank around looking at Democratic switchers — people who originally voted for passage (against Wall Street, that is), but then switched in one or more later votes to weaken. Nobody is in that particular regression who didn’t already vote against Wall Street once already, when it really counted.

I replied: Sure, but there’s still the correlation problem, in that one could argue that switchers are people whose latent preferences were closer to the middle, so they were just the ones who were more likely to shift following a change in the political weather.


Conservatism is controlled for in the analysis, using a measure derived from that Congress. This isn’t going to the middle; it’s a tropism for money. The other obvious comment is that if they are really latent Wall Street lovers, they should be moving mostly in lockstep on the subsequent votes. If you look at our summary nos., you can see they weren’t. We could probably mine that point some more.
Short of administering the MMPPI for banks in advance, are you prepared to accept any empirical evidence? Voting against banks in the big one is pretty good, I think.

Me: I’m not sure, I’ll have to think about it. One answer, I think, is that if it’s just $ given to pre-existing supporters of Wall St., it’s still an issue, as the congressmembers are then getting asymmetrically rewarded (votes for Wall St get the reward, votes against don’t get the reward), and, as economists are always telling us, Incentives Matter.


Remember those folks who turned on Swaps Push Out didn’t necessarily turn out for the banks on other votes. If it’s “weather” it’s a pretty strange weather.


  1. Ben Prytherch says:

    From the appendix:

    “As explained earlier, we tested a wide variety of variables, including various specifications of “revolving door” linkages,
    representatives’ margins of victory, and loans by financial institutions to the entire House. The variables making it into
    our final equation are these: …”

    There’s similar language for the second model, which also shows an effect of money from the finance sector on the odds of voting to weaken Dodd-Frank. It would be nice to know what happens to the estimated effects of money from the financial sector when the model specifications change. Especially considering that there are some variables chosen for one model but not the other, with no explanation given: “member of banking committee” is in the first but not the second, and “margin of victory” is in the second but not the first.

    • Jonathan (another one) says:

      +1. But to do so would be to violate the cardinal rule of academic papers: present your final model and tell the world how hard you worked to get there, but don’t bore them with details about the effect of the inclusion of “insignificant” variables.

      • Ben Prytherch says:

        Yes, or just say “we used stepwise regression”. What do you mean, what happens when I try different combinations of variables? The computer told me this is the correct one!

        Actually in this paper, the “member of banking committee” predictor was not statistically significant, but they included it in the first model anyway on the grounds that they had good reason to believe it matters. Which is commendable, I think… but then why wasn’t it in the second model too? Maybe there’s a good reason but I don’t see it in the paper.

  2. Martha (Smith) says:

    “Conservatism is controlled for in the analysis, using a measure derived from that Congress.”

    In general, I think “attempted to adjust for” is much more intellectually honest than “controlled for”.

    And why is the measure they used a reasonable choice to adjust for conservatism? Why was it chosen rather than other possible measures? What are its possible strengths and weaknesses?

  3. Xi'an says:

    Very abstract [cat picture]…!

  4. Tom says:

    One possibly subtle point. A vote to weaken Dodd-Frank isn’t necessarily a vote to help the large banks (“Wall Street”). The fixed costs in the regulation were substantial and more easily borne by large multinationals. That is why the bill had complete carve-outs for community banks. Weakening Dodd-Frank therefore reduces the cost discontinuity as mid-size banks grow, and increases competition in the top tier.

    The authors would need to parse the actual bills and estimate the anticipated effects to determine the putative benefit the banks were purchasing.

    Also, as I recall Wall Street contributions vary widely from election to election and tend to follow those who are ultimately in power. It seems more like buying goodwill than actually trying to influence votes (unlike, say, sugar producers or green energy firms). Perhaps someone else has better insight on those empirics.

    • Cody L Custis says:

      Chris Arnade makes the same case on an episode of Econtalk. Under an Arnade hypothesis, the study authors found significant results, with the opposite sign that would be expected!

    • Tom says:

      Different Tom. Definitely the case. DF and other regulation hurts small banks, given that a lot of compliance costs are fixed. But it is even worst than that. Or actually better.

      Non banks or ‘shadow banks’ are always eating away at lending from regulated banks. If you have a mortgage and a car loan, there is a good change that the mortgage was originated by a non bank, and less than half of new cars are financed by banks. Auto company captives hold a large share of loans. 30% of vehicles are leased. Maybe 15% are purchased with cash. And Credit Unions have picked up market share. And a very good chance both are securitized.

      Huge amounts of lobbying involve businesses defending their turf or interests against other businesses. Any regulatory costs that can simply be passed through to consumers are annoying but part of doing business.

      Here is a quote from a bank securities analyst:

      “Repeal Dodd-Frank? Really?

      Don’t believe anyone who is telling you that the large U.S. banks wish for a complete repeal of Dodd-Frank. What Mr. Corbat (and his counterparts) really wants for Christmas (or perhaps earlier in June) is some regulatory relief in certain key areas – specifically CCAR, Volcker rule compliance and a little less combative approach from regulators.”

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