Indulging in Confirmation Bias

For my view of the housing bubble. John Geanokoplos and others wrote,

Notice that if we freeze leverage (LTV) at constant levels, the boom gets dramatically attenuated, and the bust disappears.

This statement is based on a simulation of an “agent-based” model for house prices. Pointer from Eric Beinhocker from Mark Thoma.

Beinhocker writes,

rather than predict we should experiment. Policymaking often starts with an engineering perspective – there is a problem and government should fix it. For example, we need to get student mathematics test scores up, we need to reduce traffic congestion, or we need to prevent financial fraud. Policy wonks design some rational solution, it goes through the political meat grinder, whatever emerges is implemented (often poorly), unintended consequences occur, and then – whether it works or not – it gets locked in for a long time. An alternative approach is to create a portfolio of small-scale experiments trying a variety of solutions, see which ones work, scale-up the ones that are working, and eliminate the ones that are not.

American pragmatist John Dewey also thought that technocrats should take an experimental approach. That is not a new idea. (I learned this from Jeffrey Friedman, who sent me a draft from his forthcoming book.) Of course, my view is that I would rather see experiments come from the market than from technocrats.

Later, Beinhocker writes,

A major challenge for these more adaptive approaches to policy is the political difficulty of failure. Learning from a portfolio of experiments necessitates that some experiments will fail. Evolution is a highly innovative, but inherently wasteful process – many options are often tried before the right one is discovered. Yet politicians are held to an impossibly high standard, where any failure, large or small, can be used to call into question their entire record.

I would argue that avoidance of failure is natural in any large organization, not just government. That is why I think that markets are better able to conduct experiments to solve problems.

I found Beinhocker’s essay interesting. However, if we are going to try to improve economics, it is important to include behavioral policy-making and politics into the analysis. Do not simply assume a benevolent, rational technocrat as decision-maker.

Speaking of confirmation bias, a recent Instapundit post linked to an old essay of mine, one which speaks to this comparison between expertise mediated by markets and expertise mediated by government.

7 thoughts on “Indulging in Confirmation Bias

  1. What is debt but leveraged wealth?

    There is a difference between means and ends under current and future conditions. Markets are often better at determining the best means under existing conditions and adapting to change but encounter problems achieving the best ends when it requires establishing or altering them. Best ends does presuppose some common standard but is one we can’t necessarily escape.

  2. One of the fascinating things about the housing topic is how priors pretty much determine everything. So much of the evidence for credit-based explanations is reasoning from a price change. We should expect to see higher LTVs for 1st time buyers in any context where prices were higher, whether from supply constraints, low interest rates, or lenient credit. High LTVs is evidence of high prices, and that is all. But, we already know prices were high.
    So, when it comes to the bust, our priors are either that a bust was unnecessary or inevitable, and this is completely a product of priors.
    Overwhelmingly, the housing boom was a product of what MSA you lived in. Mian and Sufi basically adjusted that away by using county level fixed effects. The low income zip codes of the Closed Access cities were among the top national quintile of zip codes for income growth, but since there is so much income inequality in the Closed Access cities (because of the same housing constraints that led to the price bubble) when you adjust for county level trends, those zip codes look like they are very low income with negative income growth. So, areas with high income growth and expensive homes due to a massive migration of aspirational workers into the Closed Access cities end up looking like desperate places with declining incomes and rising home prices.

    There was desperation in those places, but the desperate families weren’t rabidly speculating on homes. Some were trying to hold on in LA, but many were compromising in Riverside or Phoenix, or moving farther away.

    Like you said, you have to look at this locally. Any analysis that looks at the national housing market and begins with the idea that housing expansion, high prices, and credit are correlated and unrelated to rent inflation is going to be bass ackwards right out of the gate and every subsequent round of conclusions it leads to will be 180 degrees wrong.

    • A mobility and building restriction bubble? Can you distill your main thesis to a sentence or three?

      • There was no housing bubble. There were places with high income opportunities where a lack of housing created a bidding war for access. The idea that loose credit and money created a lot of demand and price pressure was a moral panic – a figment of collective imagination. Aggregate data show nothing. But the subsequent lack of credit we have imposed on the low end market is real and obvious and it’s strangling the economy and creating high costs through rising rents.

        • But why did banks go bust?

          I always post the chart of how The Fed Funds Rate comically shot up and then plummeted, obviously causing the boom and then causing the bust. Do I finally have someone who will comment on it?

          • Exactly. The Fed inverted the yield curve by late 2005 and didn’t relent until late 2007. Clearly the CDO collapse in late 2007 was a liquidity crisis. I don’t even think that is controversial. Everyone is just so blinded to the cause of it because they are so convinced that homes had to drop that the Fed has gotten a pass. But there is only one institution that can stabilize liquidity. In August 2007 when homes had been pretty stable, they held rates at 5.25, saying inflation was their main concern and that the housing correction was “ongoing”. That’s when the bottom dropped out. Remember the Jim Cramer tantrum on CNBC around Aug 3, 2007? At the time I thought he was a goofball, but he knew exactly what was happening. Interesting to watch in hindsight.

  3. Politicians select from their portfolio of experiments, if such a portfolio even exists, according to whether it gets them money or influence. I doubt many politicians examine outcomes from an “engineering” perspective. Beinhocker euphemizes this as the “political meatgrinder”.

    Actually, politicians are held to an impossibly low standard. The American public has both a short attention span and tunnel vision. Some topic gets hot for a while and then fades away or gets overtaken by other issues.

    Rarely do the politicians or parties get punished. Example: immigration. This has managed to be important, on the right, for several election cycles. A fence is required to satisfy the base. A fence has been promised for a decade or more, but there is no fence. Finally, the party gets forced into accepting a deeply flawed candidate who says he will build a fence. But he is not yet elected and the fence not yet built.

    Supposing that the public, via vote, can discriminate between clever wonkish proposals to manage real estate bubbles is preposterous. Politicians know this. The only things that matter, at all, are: immigration; abortion; sexual liberties; religious freedoms; gun rights vs control; the price of gas; unemployment rate; and a nebulous sense of economic welfare and US stature in the world. Unfortunately, real estate bubbles add to the feeling of economic well-being while they are getting more dangerous.

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