John Kay on Financial Reform

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He writes,

It is hard enough to find people capable of running financial conglomerates – the fading reputation of Jamie Dimon, JPMorgan Chase chief executive, confirms my suspicion that managing these businesses is beyond the capacity of anyone. The search for a cadre of people employed on public-sector salaries to second guess executive decisions is a dream that could not survive even the briefest acquaintance with those who actually perform day-to-day supervisory tasks in regulatory agencies. They tick boxes because that is what they can do, and regulatory structures that are likely to be successful are structures that can be implemented by box tickers.

Kay’s views align exactly with mine. For close to five years now, I have been saying that we should not be aiming for making the financial system that is harder to break. We should aim for a system that is easier to fix.

Thanks to Alberto Mingardi for the pointer.

Two Lifted from the Comments

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1. On this post. Kebko writes,

Arnold, you have the causality backwards. The reason the standards for down payments were not reduced in the 1970′s is because the high monthly payments were the bottleneck for qualification. Reducing the down payment increases the monthly payment. But, in the 2000′s, the down payment was the bottleneck, so reducing the down payment at the expense of higher monthly payments was useful.

Comparing the two contexts, we should, in hindsight, expect that this would be an obvious paradigm shift between a high nominal rate environment and a low rate environment. The low down payments in the 2000′s are an effect, not the cause.

Certainly, reducing the down payment requirement does not cause market interest rates to be lower. So between those two variables, causality can run at most in one direction.

You are saying that the real estate industry is not going to push for lowering the down payment requirement in a high interest-rate environment. I can see that if the marginal homebuyer is low on income and low on assets. If nominal interest rates are high, the monthly payment will be daunting, and lowering the down payment requirement cannot help this person.

On the other hand, suppose that the marginal homebuyer has decent income and low assets. Even in a high interest-rate environment, lowering the down payment requirement might help that person. And if interest rates are high because of general inflation, including house price inflation, then from the bank’s point of view it is safer to lower the down payment requirement in this environment than in an environment of low inflation.

I think that the main reason that down payment requirements went down was because the people lending the money at least implicitly assumed rising house prices. In addition, government officials were beating up on lenders for rejecting applicants from what was called the “under-served” segment of the market. (Of course, by 2010, government officials described this segment as “borrowers who were not qualified” and were shocked, shocked that the evil, predatory lenders had forced these people to take loans that they could not repay.)

2. From a comment on my post on Shiller and Taleb,

Hi I am Taleb, honored to come here. The problem is more complicated. The class of proba distributions needed is restricted, so only thin-tailed ones are allowed. In other words, the law of large numbers operates too slowly to make a certain class of claims.

see:
http://www.fooledbyrandomness.com/FatTails.html

The Evolution of the Phillips Curve

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James Hamilton writes,

But as one can see from the red circles in the graph above, the expectations-adjusted Phillips Curve again seems to be missing over the last 5 years, with the observed inflation rate higher than predicted. Coibion and Gorodnichenko (2013) explore a number of possible explanations for this, including structural instability and changes in the labor market. They suggest that the best explanation is a divergence of different measures of the “expected inflation” that serves as a shift factor for the Phillips Curve. Using either the last-year’s average adjustment used in the above figures, or looking at expectations of inflation implied by the yields on Treasury Inflation Protected Securities, or expectations from the Survey of Professional Forecasters, one always finds recent inflation to have been higher than predicted by the historical Phillips Curve. But Coibion and Gorodnichenko note that these measures of expected inflation have recently diverged from the answers given by those households who are sampled in the University of Michigan’s survey of consumers. Those respondents have been consistently saying that they expect a higher inflation rate than the value implied by TIPS or professional inflation forecasters.

Read the whole thing. The charts tell a lot of the story.

In the current draft of the introduction to my macro book (and I am–once again–starting it over), I write,

If we look at the relationship between inflation and unemployment within time periods, the story is mixed. During the Forgotten Moderation, as unemployment came down, inflation increased, showing strong negative correlation. During the Great Stagflation, there is no apparent correlation, positive or negative, between inflation and unemployment. The same is true of the Great Moderation. The Financial Crisis Aftermath has only five years of data, which makes it difficult to establish correlation.

As you probably know, many macroeconomists have employed an equation (often on a diagram) that traces out a negative relationship between inflation and unemployment, and that this Phillips Curve has been at the center of controversy. I will have plenty to say about it in later chapters.

For the moment, I am just pointing out that the Phillips Curve is an example of macroeconomists using an equation that is not necessarily data driven…

The Phillips Curve began as an interesting empirical regularity, with no theoretical foundation. Milton Friedman famously said in 1967 (published 1968) that the attempt by policy makers to use it would cause it to break down. A few laters, it broke down. However, by this point, many economists had become so attached to it that they searched for new variables to add to the equation to make it work again. One of these was, in effect, the lagged dependent variable, supposedly representing “expectations.” In fact, in most economic time series, adding the lagged dependent variable improves the fit dramatically. Then you can play around with specifications to get the relationship you want between the variables you care about (in this case, inflation and unemployment).

The Phillips Curve is the archetype of Tinkerbell relationships in macroeconometrics. It is alive, but only if you believe in it.

Exit, Voice, and Secession

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Cnet has an interesting story.

The idea of techno-utopian spaces — new countries even — that could operate beyond the bureaucracy and inefficiency of government. It’s a decision that hinges on exiting the current system, as [entrepreneur Balaji] Srinivasan terms it from the realm of political science, instead of using one’s voice to reform from within, the very way Page and Brin decided to found their search giant instead of seek out ways in which the then-current tech titans could solve new problems.

Here is some Kool-Aid that I am not drinking:

With 3D printing, regulation is being turned into DRM. With quantified self, medicine is going mobile. With Bitcoin, capital control becomes packet filtering. All of these examples, Srinivasan says, are ways in which technology is allowing people to exit current systems like physical product production and distribution; personal health; and finance in favor of spaces of their own creation.

Instead, I think that secessionists are in for a tough slog. I would try to embark on the process gradually. A key step is to convince governments to unbundle their services and open them up to private competition. I know that sounds like an impossible task. But building a new society without the existing base of political norms and legal systems sounds even harder.

Democrats and Deregulation

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A commenter on an earlier post recommended a timeline created by Aaron Rodriguez that lists the attempts (mostly by Bush Administration officials) to regulate Freddie Mac and Fannie Mae. At every turn, they were blocked by Democrats. Read the whole thing. I would simply add that:

1. Even under President Clinton, Larry Summers wanted to tighten regulation over the two firms. He also recognized that their political clout was bad for the country.

2. At the time, Freddie Mac and Fannie Mae were shareholder-owned companies. If you want to maintain a narrative that the blame for the housing bubble falls on the private sector and too little regulation, they could include Freddie and Fannie in that narrative. In my opinion that would make the narrative of “not enough regulation” more intellectually respectable. But if your goal is to exonerate Democrats and blame Republicans, then you want to use the younger Tsarnaev’s defense in the Boston Marathon bombing case: Freddie and Fannie would have never gotten in trouble had they not fallen under the spell of their evil over brother, Wall Street.

What does the healthcare.gov timeline look like?

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As we have heard,

The Obama administration announced Friday that it was putting a private firm in charge of fixing its faulty health insurance Web site and set the end of November as a target date for working out all the bugs, the first indication of how long repairs may take.

I am trying to figure out the timeline. Suppose that we work backwards:

–two weeks of beta testing takes us back to November 16

–three weeks of user testing takes us back to this week

–one week of integration testing takes us back to October 20

–one week of unit testing takes us back to October 13

–one week to code fixes takes us back to October 6

–two weeks to identify problems and specify fixes takes us back to late September

What I infer is that they have had a working version of the system, not ready for deployment but ready for testing, for a few weeks now.

Otherwise, I do not think I would want to be the guy who confidently announced that the system will be functioning smoothly by the end of November.

Comparative Banking Systems

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Charles W. Calomiris and stephen H. Haber write,

The fact that the property rights system underpinning banking systems is an outcome of political deal-making means that there are no fully private banking systems; rather, all modern banking is best thought of as a partnership between the government and a group of bankers, and that partnership is shaped by the institutions that govern the distribution of power in the political system.

Read the whole thing. Another excerpt:

In 1977, Congress passed the Community Reinvestment Act to ensure that banks were responsive to the needs of the communities they served. The CRA required banks that wanted to merge with or acquire other banks to demonstrate that responsiveness to federal regulators; the requirements were later strengthened by the Clinton administration, increasing the burden on banks to prove that they were good corporate citizens. This provided a source of leverage for urban activist organizations such as the Neighborhood Assistance Corporation of America, the Greenlining Institute, and the Association of Community Organizations for Reform Now, known as ACORN, which defined themselves as advocates for low-income, urban, and minority communities. Such groups could block or delay a merger by claiming that the banks were not in compliance with their responsibilities; they could also smooth the merger-approval process by publicly supporting the banks. Thus, banks seeking to become nationwide enterprises formed unlikely alliances with such organizations. In exchange for the activists’ support, banks committed to transfer funds to these organizations and to make loans to borrowers identified by them. From 1992 to 2007, the loans that resulted from these arrangements totaled $850 billion.

In contrast,

In Canada, the government did not use the banking system to channel subsidized credit to favored political constituencies, so it had no need to tolerate instability.

Shiller, Taleb, and Me

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Here is the 30-minute version of the 2009 New Yorker video interview with Bob Shiller and Nassim Taleb. (Tyler linked to a four-minute segment a few days ago). I want to talk about the difference between Shiller’s and Taleb’s views of inefficient markets.

When I teach regression in statistics, I show what I call the Pythagorean relationship, which describes what computer programs report as the analysis of variance. You are trying to predict a variable, Y, and the predicted values along the regression line are called Y-hat. I draw a right triangle with the standard deviation of Y-hat on one side, the standard error of the regression on another side, and the standard deviation of Y on the hypotenuse. The Pythagorean Theorem then gives you the analysis of variance.

Anyway, a lesson of this is that in an efficient prediction, the variance of your prediction will be less than the variance of the variable that you predict. Mathematically, this is because one side of a right triangle is always shorter than the hypotenuse. Intuitively, if your predictions vary by more than the variable you are trying to predict, then you can do better by toning down your predictions and moving them closer to the mean of the variable.

Shiller’s insight was to apply this idea to asset prices. In some sense, the stock price is a prediction of discounted future dividends, which I will refer to as average realized dividends. In that case, if the stock market is efficient, then the variance of stock prices should be less than the variance of average realized dividends. In fact, it is easy to see that the variance of stock prices is much higher than that of average realized dividends.

What this says, and what Fama and French later confirmed, is that you can make money by betting on mean reversion in stock prices. To do so, you assume use historical average dividends as a proxy for average realized dividends going forward. If you follow a strategy of buying when prices are low relative to historical average dividends and selling when prices are high relative to historical average dividends, then it seems that you will earn an above-normal profit.

Taleb would not bet on mean reversion. Instead, he would load up on out-of-the-money options. That way, you are betting on Black Swans.

Taleb’s point of view gets back to my criticism of Shiller’s work. From Taleb’s point of view, Shiller is like the turkey, who every day notices that the farmer is feeding him and taking care of him. The turkey does not realize that Thanksgiving is coming, and this will change the farmer’s behavior. Similarly, the markets appear to be mean-reverting, but what Shiller does not know is that a Black Swan event could come along.

For example, suppose that bond market investors have a probability p of a Black Swan, meaning that the U.S. government runs out of other options and monetizes a lot of its debt, leading to hyperinflation and making long-term bonds effectively worthless. For simplicity, suppose that this Black Swan either will or will not occur on January 1, 2020. With that simple assumption, on January 1, 2020, the true value of a long-term bond will be either 100 or 0. Whichever it turns out to be, when Shiller does his analysis in 2025, he will find that the variance of the “correct” bond price is zero. Since the price of bonds between now and 2020 is a predictor of the “correct” future bond price, to be an efficient predictor its variance can be no larger than zero.

However, between now and January 1, 2020, the bond price will vary as bond market investors’ estimate of p varies. Thus, the variance of bond prices will not be zero.

I take the view that this possibility of a Black Swan (aka, the peso problem) precludes the use of realized data to construct a “variance bound.” Only in a world where you can rule out Black Swans can you be certain that Shiller has found a market anomaly.

Although I lean toward Taleb, I consider that Shiller may be right. In any case, it is worth contemplating the tension between the two.

Can I Bet These Guys?

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Clay Johnson and Harper Reed write,

HealthCare.gov needs to be fixed. We believe that in a few days it will be.

A few days?

They suggest that the government should modernize its procurement practices and development methods. On that issue, I do not disagree. But such modernization is not a magic bullet.

Johnson and Reed have experience in using the Internet to help political candidates mobilize supporters. To me, that is not the same thing as building a complex, mission-critical system to support a business.

What I am pushing is the idea that success in building such a system is not a matter of finding a technological magic bullet. It is a matter of starting with the right kind of organization on the business side. If the government is going to operate the world’s biggest health insurance brokerage, then the government needs to set up a business organization to manage it, with clear lines of authority and communication. Yes, it doesn’t hurt to use the most effective development tools and methods. But show me an ineffective org chart in the business, and I’ll show you a systems project failure no matter what tools and methods they use.

[UPDATE].

Jeff Sients, the new Suit, is not talking in terms of days, but he still seems optimistic.

Zients said healthcare.gov will be functioning “smoothly” for the vast majority of users by the end of November

The Suits are now talking about a “punch list,” as though this is a house that you just bought and the builder has to touch up the paint in a few places. For all I know, that accurately describes the situation. The worry is that instead of a basically solid building they have another Silver Spring Transit Center.

Ezra Klein interviews Fred Trotter, a health IT specialist who steers away from government contracts. Some excerpts:

I realized I could figure out how to develop these very complex, very new software programs or I could figure out how to contract with the government…One of the jokes we have in health IT that doctors have no idea what they want and we’ve been giving it to them for years. And I think that’s a fair assessment of technology procurement. The government has no idea what it wants and contractors have been giving it to them for years…There’s a problem in government IT departments in general where you get somebody who got a job in their 20s and didn’t really have any reason to improve their skill set or change their approach over 20 years but now they’re in charge of a department. People think if you are a geek and a technologist and that’s the way it is. But if I knew what I knew four years ago today and that’s all I knew today I’d be out of a job.

Market Monetarists Jump the Shark

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Scott Sumner writes,

In America mortgage debt is commonly structured so that monthly payments stay constant over 30 years. This means that during periods of high NGDP growth, when nominal interest rates are also high, monthly payments will start very high in real terms, and then fall rapidly in real terms. But your ability to qualify for a house depends on how large the initial nominal monthly payment is, relative to your current income.

Read the whole thing. The logic is this:

1. In the 1970s, house prices started rising, but they did not rise as much as during the recent bubble.

2. In the 1970s, because mortgage rates were high, even though real interest rates were low it was hard to get mortgage credit. That is what choked off the bubble. The same thing did not happen in the recent bubble.

3. High mortgage rates reflect loose monetary policy. Hence, the difference between the 1970s and the recent bubble is that this time monetary policy was tighter.

I agree that there is a “money illusion channel” between nominal interest rates and housing. Back in the 1970s, economists proposed price-level-adjusted mortgages (PLAMs) to get around this problem. If you want more background, go to MRUniversity and watch the first half-hour or so of videos from my housing course.

But….come on. The extension of the recent bubble compared to the 1970s came from the abandonment of standards for down payments. If you think that looser monetary policy would have choked off the recent housing bubble, you’ve jumped the shark.