Housing Finance and Recessions

Oscar Jorda and others write,

The rapid increase in credit-to-GDP ratios since the mid-1980s was just the final phase of a long historical process. The run-up started at the end of World War II and was shaped by a long boom in mortgage lending. One of the startling revelations has been the outsize role that mortgage lending has played in shaping the pace of recoveries, whether in financial crises or not, a factor that has been underappreciated until now.

Pointer from Mark Thoma.

When I read this, I wanted to shout “Underappreciated by who?” Maybe by the macroeconomists who were trained by Stan Fischer, Thomas Sargent, and their progeny. But until Genghis Khan pillaged macro, every macroeconomist knew that housing and mortgage credit rationing were major economic forces in the United States. Until the late 1980s, the process generating recessions consisted of interest rates rising, mortgage lenders losing deposits (because of interest rate ceilings), home buyers losing access to credit, and housing collapsing. And every macro economist knew this.

And even if you are too young to know any old-fashioned macro, you could read Ed Leamer. I would suggest that the authors of this essay try searching for Leamer Housing is the business cycle.

What this essay teaches shows to be underappreciated is Google.

Note that there is more to the essay, which Timothy Taylor found worthwhile.

Genghis Khan Lays Waste to John Taylor


Stanley Fischer said
,

a simple rule of that sort will, by necessity, leave out many factors that appropriately influence monetary policy, such as financial developments, temporary divergences in relationships between different measures of economic activity or inflation, and the like. A simple rule can provide the starting point for the decisions made by the FOMC, but in reaching their interest rate decision, members of the Committee will always have to use their judgment to identify the special circumstances confronting the economy, and how to react to them.

Pointer from Mark Thoma.

Questions for Mark Thoma

He writes,

Surprisingly, the loss of more than 800 independent banks wasn’t due to an unusually large number of bank exits during the financial crisis. Instead, it was due to a fall in bank entries, from around 100 new banks per year prior to the Great Recession to just three per year on average since 2010 (only four new banks appeared from 2011 to 2013).

1. Does too-big-to-fail play a role in this, by making it hard for smaller banks to compete? Are some conservative (e.g., Peter Wallison) complaints about Dodd-Frank reinforcing TBTF possibly valid?

2. Does the causality run the other way? That is, have business formation rates been low, and this reduces the demand for services of small banks?

These are genuine questions, not rhetorical ones–my inclination is to believe Thoma’s story. I do not know if it is possible to find data that would answer these questions, but I think that searching for answers could be interesting.

Megan McArdle on Bifurcated Family Patterns

She writes,

Could this be genetic? you ask. People who have impulse-control problems might be more likely to divorce and pass those traits on to their kids. Partially, sure. But two evidence points argue against genetic determinism. First, similar, although less severe, patterns show up in the case of kids who lose one parent, which is mostly not going to be due to homicide. And second, if this is genetic, how come it has changed over time? Have we all gotten genetically less able to stay out of jail or sustain a long-term marriage?

We know that children of single-parent households have worse outcomes than children of two-parent households. To simplify, let us say that there are favorable family patterns and unfavorable family patterns.

First question: how much of this is causal?

It could be that an inability to do well on the marshmallow test causes you to be less likely to raise children in a favorable family pattern and also more likely to pass on to your children genes that cause them to be unable to do well on the marshmallow test. That is how genetics could account for the relationship between family patterns and child outcomes.

Megan asks, what has changed over time? It could be two things. First, nowadays it may be that you have to be much better at the marshmallow test to sustain a favorable family pattern. Second, it may that we have gone through two or three generations of increasingly assortive mating.

Until 1965, a man who was in the top third on the marshmallow test might very well have been married to a woman in the bottom third, and conversely. For one thing, the top third and the bottom third were not that far apart. For another, the signals of being able to do well on the marshmallow test were not as clear (college education was too rare to be a reliable signal, particularly among women). Finally, men and women cared more about separate respective roles (breadwinner and homemaker) than about common abilities in the marshmallow test.

But in the 1960s that began to change. So you get one generation of assortive mating, and for the children of these marriages the difference between the top third and the bottom third on the marshmallow test starts to widen. Then they grow up, engage in assortive mating, have children, and difference widens once more. And so on.

But suppose we assume that there is a strong causal relationship between bad family patterns and bad outcomes. That leads to our

Second question: what can policy makers do to improve family patterns?

If anti-poverty programs are the solution, then why has the problem been getting worse? The Center on Budget and Policy Priorities (pointer from Mark Thoma) will tell you that anti-poverty programs are working to keep people out of poverty. So why are we not seeing more family stability? (Ross Douthat makes related points. Pointer from Tyler Cowen.)

Of course, there is a hypothesis, going back to Moynihan’s analysis, that anti-poverty programs are the problem, rather than the solution, because on the margin they reduce incentives to marry. I am skeptical about that, but as you know I am all for replacing current means-tested programs with a universal benefit that has a low implicit marginal tax rate. The idea is to reduce the adverse incentives that presently exist.

Megan, like Charles Murray, would like to see elites proclaim the benefits of good family patterns. I am skeptical of that, also.

My guess is that family patterns are not amenable to public policy interventions.

MIT Economics and Academic Prejudice

The MIT economics department’s dominance was fading just as I entered grad school there. David Warsh, himself a long-time chronicler of the department, reviews a book edited by E. Roy Weintraub on the golden age of economics at the Institute.

A sixth factor, advanced by Weintraub in the Transformation volume, argues that the rise of MIT stemmed from its willingness to appoint Jewish economists to senior positions, starting with Samuelson himself. Anti-Semitism was common in American universities on the eve of World War II, and while most of the best universities had one Jew or even two on their faculties of arts and sciences, to demonstrate that they were free of prejudice, none showed any willingness to appoint significant numbers until the flood of European émigrés after World War I began to open their doors. MIT was able to recruit its charter faculty – Maurice Adelmam, Max Millikan, Walt Rostow, Paul Rosenstein-Rodin, Solow, Evsey Domar and Franco Modigliani were Jews – “not only because of Samuelson’s growing renown,” writes Weintraub, “…but because the department and university were remarkably open to the hiring of Jewish faculty at a time when such hiring was just beginning to be possible at Ivy League Universities,”

Pointer from Mark Thoma. My Swarthmore College professor Bernie Saffran emphasized the anti-Semitism factor also. Bernie’s version was that Harvard’s anti-semitism made Samuelson feel that he would be better off at MIT, and once he went to MIT he went about using Jews to build a superior department to pointedly punish Harvard. It took almost three decades (roughly from the end of World War II to the late 1970s) for Harvard to come back.

Economists generally view prejudice by a firm as unsustainable, because that firm will lose out to competitors. The lesson I take from the Harvard-MIT story is that in academia prejudice can persist for a while, with long-term detrimental effects. Consider that as you read stories about prejudice against conservatives.

Read Warsh’s entire article, which covers much more ground.

UPDATE: For more on the economics of discrimination, check out the links on David Henderson’s post.

Marginal vs. Average Debt to Equity in Housing

Alejandro Justiniano and others write,

if the relaxation of collateral constraints had been widespread, it should have resulted in a surge of mortgage debt relative to the value of real estate.

In the data, however, household debt and real estate values rose in tandem, leaving their ratio roughly unchanged over the first half of the 2000s, as shown in Figure 3. In fact, this ratio only spiked when home prices tumbled starting in 2006.

Pointer from Mark Thoma.

Suppose that back when lenders asked for 20 percent down, three families bought houses for $100,000 each and put $20,000 down each. Total mortgage debt is $240,000 and total home values are $300,000. The ratio of household to real estate debt is 80 percent.

Next, lenders allow someone to buy a house with no money down. As a result, home prices rise to $130,000. Adding $130,000 debt to the debt of the other three households (ignoring any equity they may have built up through paying down mortgage principal), we have total mortgage debt of $370,000. But total home values are $520,000, so that the average ratio of debt to equity has actually fallen, to just over 70 percent.

As long as home prices are rising, the last thing you should expect is for the average debt to equity ratio to rise. The fact that it did not fall is an indication of how powerful the boom in credit was. Only if you use a silly representative-agent model, in which there is no difference between average and marginal borrowers, would you predict something different. I have not read the paper, but I suspect that is what the authors did.

Macroeconomics and Expertise

As part of a general blog conversation, Noah Smith writes,

Scott Sumner expresses incredible confidence that NGDP targeting is best. Paul Krugman expresses incredible confidence that fiscal stimulus is effective and that austerity is counterproductive. John Cochrane expresses incredible confidence that structural form – removing “sand in the gears” – is the best medicine for an economy in recession. Robert Lucas said that the “central problem of depression prevention has been solved.” And so on, and so forth.

I think normal people realize that that certitude is basically never warranted. Yes, those economists often (but not always) have some evidence to back up their claims. But not the kind of evidence that people have in disciplines where data is more abundant, controlled, and replicable.

Pointer from Mark Thoma. I disagree that this is how normal people think. I believe that the main problem with non-expert opinion in macroeconomics is that normal people can be just as dogmatic in their macro views as self-proclaimed experts.

I would amend the last paragraph to substitute “thoughtful economists” for “normal people.” With that amendment, the quoted passage would have my vote.

Campus Bias

Daniel Little writes,

For anyone who cares about universities as places of learning for undergraduate students, Gross’s book is an encouraging one. He provides a clear and convincing explanation of the mechanisms through which a non-random distribution of political attitudes wind up in the population of university and college professors, and he provides strong evidence against the idea that universities and professors exercise discriminatory bias against newcomers who have different political identities. And finally, Gross’s analysis and my own experience suggests that professors generally conform to Weber’s ethic when it comes to proselytizing for one’s own convictions in the classroom: the function and duty of the professor is to help students think for themselves

Pointer from Mark Thoma. Not surprisingly, I disagree. One anecdote I tell is from the graduation of one of my daughters. The main graduation speaker mentioned that she had just seen in article saying that the population of the U.S. will be majority-minority by 2050. The students erupted into whooping and wild cheering.

To me, the demographic projections are facts rather than cause for joy or sorrow. But after four years of being told that white people are the oppressors and minorities are the oppressed, the students reacted automatically and emotionally. To me, it was the opposite behavior of someone who has been taught to think for themselves.

If liberal professors are not aware of political bias in their workplace, it is because, like fish, they are swimming in it. The indoctrination into the language of oppressor-oppressed is pervasive. If you don’t buy into the progessive mindset, then you feel about as comfortable on a liberal college campus as an atheist in a seminary.

The Technocrat’s Creed

He writes,

The near-global stagnation witnessed in 2014 is man-made. It is the result of politics and policies in several major economies — politics and policies that choked off demand. In the absence of demand, investment and jobs will fail to materialize. It is that simple.

Pointer from Mark Thoma.

Several years ago, I noticed

Stiglitz always writes as the omniscient observer. He knows exactly what should have been done

The creed of the technocrat, particularly as believed by Stiglitz might be something like this:

I am infallible. I can solve any problem. Given the authority, I can optimize any situation. When bad outcomes occur, these invariably come from policies that deviate from what I know to be optimal. The only thing that stands between reality and economic nirvana is opposition to me, which comes from economists who are too blind to see the correct ideas or from politicians who are too evil to implement them.

When it comes to other mainstream economists, Stiglitz is capable of spotting weaknesses in their point of view. He can be quite insightful in that regard. But if he has ever admitted being wrong himself, or even in doubt, I have not seen it.

Andrew Gelman is Too Glib

Not in general, but in this post, where he writes,

I’d like to flip it around and say: If we see something statistically significant (in a non-preregistered study), we can’t say much, because garden of forking paths. But if a comparison is not statistically significant, we’ve learned that the noise is too large to distinguish any signal, and that can be important.

Pointer from Mark Thoma. My thoughts:

1. Just as an aside, economists are sometimes (often?0 guilty of treating absence of evidence as evidence of absence. For example, if you fail to reject the efficient markets hypothesis, can you treat that as evidence in favor of the EMH? Many have. Similarly, when Bob Hall could not reject the random walk model of consumer spending, he said that this was evidence in favor of rational expectations and consumption smoothing.

2. I think that a simpler way to make Gelman’s point would be to say that passing a statistical significance test is a necessary but not a sufficient condition for declaring the evidence to be persuasive. In particular, one must also address the “selection bias” problem, which is that results that pass significance tests are more likely to be written up and published than results that fail to do so.