Monthly Archives: October 2013

The 1950s and the Tea Party

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Cass Sunstein writes,

We can’t easily understand those accusations, contemporary conservative thought or the influence of the Tea Party without appreciating the enduring impact of the Hiss case.

I think that David Halberstam’s analysis of the conflict within the Republican Party between the urban establishment and small-town populists better captures the origins of the Tea Party. In his highly perceptive 1993 volume, The Fifties, Halberstam writes (p.4-5),

On one side were the lawyers and bankers of Wall Street and State Street, their colleagues through the great Eastern industrial cities, and those in the powerful national media, based in New York. They were internationalist by tradition and by instinct: They had fought against the New Deal in states where the power of labor was considerable but had eventually come to accept certain premises of the New Deal. By contrast, the Republicans of the heartland…were anxious to go back to the simple, comfortable world of the twenties…They had always controlled their political and economic destinies locally…Now they looked at Washington and saw the enemy…they seemed to have lost control of their own party…they were at war with the Eastern Republicans, who in their eyes, were traitors, tainted by cooperation with the New Deal.

The Tea Party of the 1950s spurned Nelson Rockefeller and nominated Barry Goldwater, with disastrous electoral results.

I would reiterate that midcentury politics revolves around socialism, Communism, and anti-Communism. Both sides have history that they would rather forget. The left would rather forget that many of its leading intellectuals saw Communism as equivalent to, or even superior to, capitalism. The right would rather forget its hostility to Civil Rights (the urban Republicans were crucial to passing Civil Rights legislation, overcoming Southern Democrats and heartland Republicans.)

Extortion vs. Trade

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Apropos Halloween, George Paci writes,

Thursday, American children will be going door-to-door making notional
threats in exchange for sugary foodstuffs. (This may or may not be a
good analogy for a particular popular political stance.)

Friday, American children will be making piles out of their loot:
stuff they want to keep, and stuff they want to swap for treats they
actually like. They will then commence creating and participating in
a market, trading things they don’t want for things they want, negotiating
exchange rates between various bite-size currencies, and sometimes
trading things they do want for things they want more, or for more of
something else they want.

They do this entirely out of self-interest: because it will increase
their happiness. No adult needs to coerce them into trading, or
even suggest or facilitate it.

There is no better day to teach kids about the benefits of trade (and
about subjective value), so I propose we promote November 1 as
Benefits from Trade Day.

Sentences to Ponder

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From Robert Wright.

Self-doubt can be the first step to moral improvement. But our biases are so subtle, alluring, and persistent that converting a wave of doubt into enduring wisdom takes work. The most-impressive cases of bias neutralization I’m aware of involve people who have spent ungodly amounts of time—several hours a day for many years—in meditative practices that make them more aware of the workings of their minds. These people seem much less emotion-driven, much less wrapped up in themselves, and much less judgmental than, say, I am. (And brain scans of these highly adept meditators have found low levels of activity in brain networks associated with self-regarding thought.)

Read the whole thing. I think he is saying that utilitarianism is insufficient as a moral framework, because utilitarians with too much hubris can be morally dangerous. Maybe you will read him differently.

When Will the ACA Exchanges Be Working?

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Tyler Cowen writes,

The exchanges will be mostly working by March 2014, but by then the risk pool will be dysfunctional. In the meantime, real net prices will creep up, if only through implicit rationing and restrictions on provider networks. The Obama administration will attempt to address this problem — unsuccessfully — through additional regulation.

I disagree with the March 2014 date. My opinion of the distribution of likely outcomes is that it is bimodal. There is a high probability that the exchanges will be working at the end of November. I think that there is an even higher probability that they will be working never.

Why the end of November is plausible:

1. We may be hearing overly dire descriptions of the state of the system. Anyone from the outside who looks at a system will think it cannot possibly work. I once worked with a CIO who said that one of his iron laws was that anyone new on a systems project would say, “The person who originally designed this system was an idiot.”

2. Jeff Zients, the new manager, put a stake in the ground for late November. If he thinks that it is unlikely, he is, if nothing else, taking big personal risk to his own reputation.

3. CMS, the agency that was in charge, is actually a pretty effective group. They also pulled off something similar in implementing the Medicare prescription drug plan. It is plausible that they anticipated the major problems, and only minor fixes are now needed.

Why “never” is even more plausible:

1. The fundamental challenges may be very great. In the worst case, suppose that some of the legacy systems that the ACA web site has to access were built around 1975. Back then, in order to pull data out of such a system, you wrote a SAS program, put it into the queue of an IBM-370, waited for an operator to mount a data tape, and if all went well (no JCL errors, no logic errors in your SAS code), after a couple of hours you had a nice fat printout. Now, we want to be able to query those systems in real time, with perhaps hundreds of queries arriving at once…..Hmmm, maybe not even hotshot web programmers wielding the latest methodological buzzwords can pull that off so easily

2. While the Suits talk about bugs or glitches, it looks to geeks as though the problem is design flaws. Those are very hard to fix, particularly in a system that is so large already. Everything about the existing design is there for a reason. It may not be a good reason, but if you “fix it” without understanding the reason, you could be in for a nasty surprise. I just don’t see how you fix design flaws in four weeks.

3. Everyone says that there was not sufficient time to test the system before putting it into operation. Between now and the end of November, it does not seem as though there is sufficient time to test any major changes to the system. If you redesign parts of the system, then you have to write a test plan that is appropriate for the new design. Four weeks may not even be enough time to write a good test plan, much less carry it out.

4. If it is still broken at the end of November, the chances increase that starting over is the fastest path to a working system. But starting over requires a stronger political consensus in favor of the policy that the system is supposed to implement. And we do not have that.

Megan McArdle has more comments, focusing on the disconnect between thinkers and doers in the Obama Administration.

Macroeconomics Without P

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Scott Sumner writes,

I frequently argue that inflation is a highly misleading variable, and should be dropped from macroeconomic analysis. To replace it, we’d be better off looking at variables such as NGDP growth and nominal hourly wage rates.

If we cannot measure P tolerably well, then it sort of spoils the fun about talking about the real wage, the real money supply, or real GDP. I think that the consequence is that we shift all of the focus to:

— the average nominal wage rate, W
–total employment (or hours worked), N

The product of the two, WN, becomes aggregate demand (with NGDP an approximate indicator).

Aggregate supply determines the division between the two. For example suppose we have sticky nominal wages, with W depending on W* (what workers expected W to be, based on recent trends in nominal wages) and N (as employment gets closer to full employment, workers start to expect higher wages). We could have N affect the shape as well as the level of supply curve. That is, the effect of a change in N on wages could be low in a recession and higher near full employment.

From the Fred database, I have downloaded total compensation from the national income accounts (WN, in effect). And I downloaded total payroll employment from the establishment survey (N, in effect). The ratio of the two gives W. Some recent data on the percent change of these numbers.

Year WN percent change W percent change
2008 2.3 2.9
2009 -3.6 0.8
2010 2.3 3.1
2011 3.9 2.7
2012 4.0 2.3

Over the last five years, the median value for the percent change in nominal compensation has been only 2.3 percent. during the entire Great Moderation (1986-2007), there was only one year where nominal compensation grew by less than 2.3 percent (it was 1.6 percent in 2002). The median during the Great Moderation was 5.2 percent. Using this as a measure of aggregate demand shows weakness. Of course, any product involving N would show weakness, so don’t get too excited, folks.

The Phillips-Curve half of the story does not go as smoothly. Perhaps the 2009-2010 pattern is a fluke, and you should just average those two numbers? In any event, we had higher wage growth throughout most of the Great Moderation, but not all of it. From 1993-1996, annual wage growth was 2.1 percent, 1.8 percent, 2.1 percent, and 3.1 percent, respectively. What caused that episode of sluggish wage growth? In that case, it was not weak aggregate demand.

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.