Momentum for evidence-based policymaking is building at all levels of government, from federal legislation funding rigorous evaluations to the bipartisan Commission on Evidence-Based Policymaking to counties looking to make funding decisions based on results.
I am afraid that my reaction is to be cynical. When you make funding decisions for programs based on evidence, what will change will be the reported evidence, not the programs.
During the Vietnam War, Secretary of Defense Robert McNamara was famous for demanding statistical evidence that strategies were working. He got what he was asking for, but the statistical evidence did not capture what was really happening.
To cite another example, the Stiglitz-Orszag paper on Fannie Mae and Freddie Mac appeared to be evidence-based. Recall that they wrote,
This analysis shows that, based on historical data, the probability of a shock as severe as embodied in the risk-based capital standard is substantially less than one in 500,000 – and may be smaller than one in three million. Given the low probability of the stress test shock occurring, and assuming that Fannie Mae and Freddie Mac hold sufficient capital to withstand that shock, the exposure of the government to the risk that the GSEs will become insolvent appears quite low.
Within any organization, including a profit-seeking business, one has to be cynical about “evidence.” Show me a CEO who always believes every report he or she receives from middle management, and I will show you a company that is at high risk for going bankrupt very soon. I have never been a large-company CEO, but if I were I would make a point of setting up internal checks and balances so that I did not have to rely on any one set of carefully crafted reports.
You are entitled to ask, “How can you be against evidence? Evidence is bound to make policies better than if evidence is ignored.”
My response is that I am afraid that evidence will be distorted to make spending programs and regulations appear better than they really are. I will take public choice theory over misleading evidence, any day.
That’s very nice, and it’s the long version. The short version is, ‘If what you count is beans, beans is what you’re gonna get’.
While your broader point is well taken, I would suggest that, despite the fact that Fannie Mae was exposed to a multi-sigma event in home values, they were never either illiquid nor insolvent. The cash infusion from the federal government only served to meet the regulatory capital requirement, but none of that cash was ever needed to make a coupon payment.
Their capital was hit at the time of conservatorship because they were required to write off tax assets, which, in hindsight, was clearly too pessimistic.
It’s difficult to know how the counterfactuals would have come out if they had not been taken into conservatorship.
But, in the version of events that we experienced, less than two weeks after conservatorship, when they had been required to write off those tax assets – the accounting equivalent of suggesting that millions of foreclosures were yet to come and they could expect never to be profitable again for many years – the Federal Reserve held the Fed Funds Rate at 2%, citing inflation concerns. I don’t know how one hand of the government could demand those write downs while another hand was worried about inflation. Most defaults came after that Fed meeting. It wasn’t 2006-2007 that ended up hurting them. It was 2008-2009, after the nominal GDP collapse and after post-conservatorship GSE credit policies pulled the rug out from under the low end housing market. (Most of the price decline in the low priced housing markets most at risk of default happened after Sept. 2008.)
Even with all that said, I don’t see how the government cash infusions were ever necessary at all. The GSEs had plenty of liquid assets on their books and they have been making higher profits than ever for the past several years.
Y’know, sometimes evidence is not distorted, it is based on false facts.
The humorous part of this neverending story of government manipulation is that, in the case of the GSEs, the false facts were due to the fraud of the private investment banking system.
If the GSEs had not been taken into conservatorship their obvious actions would have been to take the investment banks to court. And the obvious end result of that would have been the destruction of the US banking system.
Read the FCIC report. The fraud of the investment banks are detailed.
All the evidence in the world, however valid, can’t change the fact that most government policies create winners and losers. But that’s all right with the social engineers who believe, mistakenly, in a social-welfare function in which A’s higher taxes are somehow offset by B’s benefits and the creation (or maintenance) of government jobs.
Yeah,
Strangely enough I do not hear many complaints about the government jobs that are created by protecting property rights.
Meanwhile, campaigns have become as fact free as anytime in history.
On the contrary, they are more empirical than ever, at least, when it comes to the science of winning elections.
I guess voters prefer feelings over facts which are easier facts campaigns can exploit through feelings.
We’ve had “evidence based” government nutritional advice for a long time. So many bits of advice have been reversed so often, I can’t tell what’s supposed to be good or bad anymore.
There’s also a “replication crisis” in other disciplines, but for a while, all those findings and any policies based on them were “evidence based”.
Of course any policy relying on forecasts using “evidence based” modeling is worthy of presumptive skepticism. At the very least, one would like to use a weighting factor based on past track record to know how confident one can be in those predictions.
I’ll give you a typical government example – project estimates. The “funny because it’s true” joke is that government building projects almost never come in on time or under budget. Is estimating the cost or duration of a construction project not “evidence based”? Certainly it is, but the evidence-based forecast almost always comes out unrealistically rosy.
This post sounds a lot like what Charles Peters used to say in his old Washington Monthly.
You might want to check out Cathy O’Neil’s new book, Weapons of Math Destruction. Lots going on, but a simple summary is that despite popular conception, data is never objective. She blogs at mathbabe.org.