Full disclosure: I’ve known Amar Bhide for roughly 25 years (we both worked on the Citibank account at McKinsey, albeit never on the same project) and although we correspond only occasionally, I continue to regard his as a particularly keen observer and original thinker. He was briefly a proprietary trader, then an associate professor at Harvard Business School (first in finance, later in enterpreneurship), then a professor at Columbia’s business school, and after taking a sabbatical to write a book (A Call for Judgment, due out in two weeks) is joining the Fletcher School of Law and Diplomacy in a newly-established chair.
Amar has an article at the Harvard Business Review which encapsulates some of the core arguments from his book. I’m providing a few extracts here because it appeals to my sensibilities and I therefore think NC readers will like it as well. The most interesting bit to me is the aspect that I highlight in the headline to this post: that the evolution of finance, particularly in its near universal adoption of standardized models in lending processes bears a troubling resemblance in its process and outcomes to a centrally planned economy (funny that people like to dump on the Fed for interest rate setting, and miss the other. widespread aspects of de facto centralization, via standardization and over-reliance on models). Some of his arguments overlap ones I’m made repeatedly here. For instance, I’ve decried the fact that shifting lending from loan officers in branches to standardized, score-based templates resulted in considerable loss of information: face to face assessment of the borrower (does he understand what he is getting into? Does he regard the loan as a serious commitment?) and knowledge of the community (How healthy is his employer? What is the outlook for the local economy?)
Bhide comes to similar conclusions to ones reached here and in ECONNED, and his framing may help finance skepticism get greater traction. From his HBR article:
Because natural laws and mathematical inferences cannot predict behavior, algorithms are built upon statistical models. But for all their econometric sophistication, statistical models are ultimately a simplified form of history, a terse numerical narrative of what happened in the past. (The simplifying assumptions of most statistical models are in fact so great that they can almost never be used successfully to reconstruct the very historical data used to construct the models.) They reveal broad tendencies and recurring patterns, but in a dynamic society shot through with willful and imaginative people making conscious choices, they cannot make reliable predictions….
This doesn’t mean statistical controls and data-mining programs are useless in human affairs. They can debunk false assumptions and stereotypes or suggest new rules of thumb. Faced with a large number of choices (as when thousands apply for one job), they can provide a quick, objective first-cut screen. But predictions of human activity based on statistical patterns are dangerous when used as a substitute for careful case-by-case judgment. They nonetheless continue to gain ascendency. Nowhere has this been more apparent—or more dangerous—than in the financial industry…..
The traditional lending model was built around case-by-case judgment. Home buyers would apply for loans from their local bank, with which they often had an existing relationship. A banker would review each application and make a judgment, taking into account what the banker knew about the applicant, the applicant’s employer, the property, and conditions in the local market. The banker would certainly consider history—what had happened to housing prices, and the track record of the borrower and other similarly situated individuals. But good practice also required forward-looking judgments—assessments of the degree to which the future would be like the past. Dialogue and relationships were also important: Bankers would talk to borrowers to ascertain their beliefs and intentions. And staying in touch after the loan was made facilitated judgments about adjusting terms when necessary….
Over the past several decades, centralized, mechanistic finance elbowed aside the traditional model. Loan officers made way for mortgage brokers. At the height of the housing boom, in 2004, some 53,000 mortgage brokerage companies, with an estimated 418,700 employees, originated 68% of all residential loans in the United States. In other words, fewer than a third of all loans were originated by an actual lender. The brokers’ role in the credit process is mainly to help applicants fill out forms. In fact, hardly anyone now makes case-by-case mortgage credit judgments. Mortgages are granted or denied (and new mortgage products like option ARMs are designed) using complex models that are conjured up by a small number of faraway rocket scientists and take little heed of the specific facts on the ground….
The buyers of securitized mortgages don’t make case-by-case credit decisions, either. For instance, buyers of Fannie Mae or Freddie Mac paper weren’t, and still aren’t, making judgments about the risk that homeowners would default on the underlying mortgages. Rather, they were buying government debt—and earning a higher return than they would from Treasury bonds. Even when securities weren’t guaranteed, buyers ignored the creditworthiness of individual mortgages. They relied instead on the models of the wizards who developed the underwriting standards, the dozen or so banks (the likes of Lehman, Goldman, and Citicorp) that securitized the mortgages, and the three rating agencies that vouched for the soundness of the securities.
Dispensing with judgment has also helped funnel the mass production of derivatives into a few mega-institutions, posing systemic risks that their top executives and regulators cannot control.
Little good has come of this robotization of finance. Reduced case-by-case scrutiny has led to the misallocation of resources in the real economy. In the recent housing bubble, lenders who, without much due diligence, extended mortgages to reckless borrowers helped make prices unaffordable for more prudent home buyers.
The replacement of ongoing relationships with securitized, arm’s-length contracting has fundamentally impaired the adaptability of financing terms. No contract can anticipate all contingencies. But securitized financing makes ongoing adaptations infeasible; because of the great difficulty of renegotiating terms, borrowers and lenders must adhere to the deal that was struck at the outset. Securitized mortgages are more likely than mortgages retained by banks to be foreclosed if borrowers fall behind on their payments, as recent research shows.
When decision making is centralized in the hands of a small number of bankers, financial institutions, or quantitative models, their mistakes imperil the well-being of individuals and businesses throughout the economy. Decentralized finance isn’t immune to systemic risk; individual financiers may follow the crowd in lowering down payments for home loans, for instance. But this behavior involves a social pathology. With centralized authority, the process requires no widespread mania—just a few errant lending models or a couple of CEOs who have a limited grasp of the risks taken by subordinates.
Yves here. This is a particularly succinct indictment of modern finance. It’s unlikely to get the traction it deserves because no new paradigm is waiting in the wings. As Thomas Kuhn argued in his Theory of Scientific Revolutions, scientific (and by implication, intellectual) frameworks persist even as evidence against them mounts, with ever-more patches and work arounds, until a new generation embraces a different paradigm.
But modern finance is a sort of lingua franca, computationally convenient, and most important, a lot of people have businesses deeply embedded in the current way of doing things. And the regulators are just as deeply invested. I found this section of a recent New York Fed paper on the shadow banking system simply astonishing (I’ve wanted to shred other significant elements of this article, but that is a serious undertaking that has to wait a bit). It listed the advantages of securitazation….without offering a list of disadvantages. To wit:
There are at least four different ways in which the securitization-based, shadow credit intermediation process can not only lower the cost and improve the availability of credit, but also reduce volatility of the financial system as a whole.
First, securitization involving real credit risk transfer is an important way for an issuer to limit concentrations to certain borrowers, loan types and geographies on its balance sheet.
Second, term asset-backed securitization (ABS) markets are valuable not only as a means for a lender to diversify its sources of funding, but also to raise long-term, maturity-matched funding to better manage its asset-liability mismatch than it could by funding term loans with short-term deposits.
Third, securitization permits lenders to realize economies of scale from their loan origination platforms, branches, call centers and servicing operations that are not possible when required to retain loans on balance sheet.
Fourth, securitization is a potentially promising way to involve the market in the supervision of banks, by providing third-party discipline and market pricing of assets that would be opaque if left on the banks’ balance sheets.
Yves here. Notice the Panglossian subtext: everything is for the best in this best of all possible worlds of securitization. Not only is there no consideration of the downside, such as the near-impossibilty of dealing with troubled borrowers on a case-by-case basis, but there is no acknowledgement that the same benefits could have been achieved by other, sometimes cheaper, means.
For instance, the first advantage, greater diversification, can be achieved by a less costly route, by selling loans. The second finesses the real problem with mortgages, that the US is pretty much alone among advanced economies in offering thirty year fixed rate mortgages on a large scale basis. Floating rates are the norm elsewhere.
A fixed rate mortgage made sense in a low interest rate volatility environment, but the product continues to exist when its effect is to shift interest rate risk on to banks, who in turn blow up on it periodically (first the savings and loan crisis) and leave taxpayers with losses. So ultimately, it isn’t banks that bear the interest rate risk, but the taxpayers who backstop banks. How sensible is this? What about a compromise, like floating rate mortgages with floor and ceilings (for example, if you got a 4.5% floater now, its floor might be 2.5% and its ceiling might be 6.5%). That way, borrower still can make sensible budgets, since their exposure is capped, but they bear a fair bit of the risk of interest rate movements.
Point three is about the cost savings from standardization and scale, when as anyone who has dealt with a servicer can tell you, it is often at the expense of service quality.
Point four, which is a naive recitation of the canard that investors can supervise banks, is refuted by Bhide’s piece. Supervision was not done in a decentralized way; instead, the greater complexity of structured credit products led investors to rely on expert opinion (ratings agencies) and models. From a related comment by Donald MacKenzie in today’s Financial Times:
The languages of today’s complex financial markets often consist not simply of words and numbers but also of technical systems. The credit crisis has shown the importance of their powers – and limits.
Although few outsiders have heard of it, the single most important language of mortgage-backed securities and similar products is a system called Intex. It includes a computer language for defining deals’ intricate cash flow rules, a graphics-based tool for designing deals, and a truly remarkable computerised “library” of the parameters of the underlying asset pools and the cash flow rules of more than 20,000 deals….
Intex’s power as a language is to make instruments such as mortgage-backed securities mentally tractable. I confess I’ve always found them daunting. The rules governing a deal can occupy hundreds of pages of impenetrable legal prose, and the economic value of the deal’s tranches depends on three complex characteristics of the underlying mortgage pool: the rate at which borrowers prepay (redeem their mortgages early), their propensity to default, and the loss severity (the proportion of the debt that cannot be recovered if a borrower defaults).
In July a friendly banker showed me Intex in action. He chose a particular mortgage-backed security, entered its price and a figure for each of prepayment speed, default rate, and loss severity. In less than 30 seconds, back came not just the yield of the security, but the month-by-month future interest payments and principal repayments, including whether and when shortfalls and losses would be incurred. The psychological effect was striking: for the first time, I felt I could understand mortgage-backed securities.
Of course, my new-found confidence was spurious. The reliability of Intex’s output depends entirely on the validity of the user’s assumptions about prepayment, default and severity. Nevertheless, it is interesting to speculate whether some of the pre-crisis vogue for mortgage-backed securities resulted from having a system that enabled neophytes such as myself to feel they understood them.
Yves here. It may seem churlish to point fingers at Intex (“Its’ a tool! You can have operator error with any device”), but pervasive use of models allows people to think all too superficially about situations. I noticed a marked decay in the understanding of businesses when PCs became widespread. Yes, doing projections and multiple scenarios became trivial. But in the stone ages of finance, bankers and analysts had to look at financial statements and go into footnotes to find details to put into spreadsheets, and they had to do any massaging to make the presentation comparable themselves. The grappling with the data produced a far greater appreciation of what the underlying reports actually contained, and also meant any scenarios were thought about before being analyzed and any not-pretty results were given more serious consideration. Now, it’s trivial to keep tweaking a model until it tells the story needed to support a sales pitch. The degree of abstraction has made it all to easy to airbrush risk out.
To return to Bhide, his piece provides further grist for thought, and I hope you will read it in full.
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Bailout America (and globalized finance) is a command economy, although structurally it’s fascist rather than Stalinist, since it maintains private profit extractors.
On the other hand all the rhetoric about “growth” and size and “scale” for their own sakes, as in the Fed paper, are characteristically Stalinist.
Corporatism of any color is of course the mortal enemy of the quality-based practices the paper and the post eulogize.
And this kind of drivel:
Fourth, securitization is a potentially promising way to involve the market in the supervision of banks, by providing third-party discipline and market pricing of assets that would be opaque if left on the banks’ balance sheets.
is the kind of thousand-times disproven corporatist talking point which signals that you can disregard the entirety of whatever communique it’s from as nothing but a pack of lies.
We know for a fact that no one in government or “the market” can “regulate” oligopoly rackets. The only options are to live under their tyranny or destroy them completely.
That’s the only way to bring back quality-based practices.
Excellent post.
I have a couple of acquaintances, here in Spain, who are predicting exactly the kind of paradigm shift towards loan-decision de-centralization, old-fashioned interviews and individual analysis, etc.
Their business idea is to provide “financial-image” services, i.e. manage the company’s image through the documentation it presents to banks (e.g. making clear how neat and safe they are through carefully selected text, stats and images).
That may be an interesting business opportunity in the US, if the trend towards de-centralized decision-making holds true.
I agree. That is one piece of the puzzle. I wonder if Yves can put us together?
Ooh, very interesting, thanks.
On a related note, I’m entering graduate school and was recently looking for a home. My father was trying to get a line of credit(or preapproval) and consistently banks used the excuse of his credit score(it’s in the lower 700s) to justify saying they either couldn’t give him a loan or had to give it to him at a higher interest rate. What drove me crazy is that rather than look at it at a case by case basis they were using that completely arbitrary score to judge his creditworthiness. What’s funny is that their is absolutely nothing bad in his credit REPORT save for a mistake that happened 4-5 years ago(by a company, not my dad, and it’s something SMALL) and they(the loan officers) seemed to be dumbstruck every time they were told to look at that rather than the simple score(the low score is due to a recent REFINANCING and a generally higher loan to income ratio).
Of course no two credit scores are equal if you don’t have the income. For example, I have a credit score in the 800s despite the fact that I am only 24 years old, but there is no chance that I could get a loan despite the fact I am seemingly trustworthy(and seemingly smart with money). This mechanization is truly against the public good.
Anyhow, just wanted to share how ridiculous I thought it was. Yves, I seriously doubt that a floating rate environment such as the one you outlined here would ever hold in this for profit industry: I’ve looked at many supposedly floating rate loans, and I’ve found that their floor is always set at a high rate. For example, if the Fed funds rate is at or near 0% they still charge at the least 3.5%, rather than something like 2.5%. You can look at rates today and see just this…for I was telling my dad that he shouldn’t refinance(many many months ago) because I felt that the environment wouldn’t pick up based on what I was reading. However, when I found out he was still paying 3.5% or more I couldn’t help but shake my head.
-DJ
BTW I realize the article above was towards MBS and other securitizations in general….just thought I’d make an example on a much much smaller scale :D
And when you reflect on the fact that the bank is borrowing between 0.0% and 0.25% you will no-doubt be shaking your head even more! US finance has become a global casino; Gresham’s law on a grand scale.
I should have mentioned that in New York City in the early 1980s, floaters like I described were the ONLY type of mortgage you could get on cooperative apartments. So the product existed, and was profitable in the higher cost environment of unsecuritized finance (and when interest rate swaps were a new product, hence probably more costly too).
I obviously don’t recall the terms, but I would be pretty certain they had significant penalties for refis.
While I don’t doubt that some ostensibly more sophisticated investors were lulled into a false sense of security by tools like Intex (disclosure – the company I work for owns a rival SF technology company), I don’t think it was more than a contributing factor. The real problem (on the buy side) was investors who didn’t even use Intex or comparable tools and never even went to the trouble of coming up with assumptions about loss severity or default timing, just relying on the rating. That’s not to say there aren’t problems with tools like Intex – until now, the companies that make them have had to construct the waterfall models by hand, and if all the underlying documents aren’t available, they have to make assumptions about things like swap terms which can have a huge effect on how deals perform in unusual circumstances. This is one area where the recent SEC reforms should make a big difference.
When the assumptions are bad, tools like Intex are every bit as bad as the ratings stamped onto those securities(and perhaps worse). The value of programs like those only come through the quick SUPPLEMENTAL information it spits out…as Yves noted above, using it as a means to an ends is, overall, dumb.
The final paragraph of this excellent post should be printed and pasted over every college computer screen.
I work with documents produced in other languages and reading summaries or abstracts simply doesn’t produce the same level of understanding as working with pencil and paper.
Copying key passages helps me internalize the information. It’s a different kind of kinetic-neurological activity and produces much better results. I also like to go for long, daily walks which help as well.
I’ve experienced these dynamics, as well.
Excellent point.
The ‘robotization of finance’ would work perfectly well if we were all robots.
One of the key items missing in the current economic paradigm that Bhide (and Yves) describe is an absence of ‘the human factor’.
@Recovering Investment Banker’s comment certainly underscores this ‘human factor’; it’s costly and inconvenient in today’s paradigm. People don’t like complexity (education researchers can explain why, but it’s a huge digression so I will spare you.) Great comment, @RIB, although I physically cringed as I read it.
I suspect that ‘the human factor’ will be essential to building a better, newer economic paradigm. The key seems to be bringing things down to a more manageable scale, to personal interactions.
It would seem that @Diego Méndez knows people who, without discussing economic paradigms in formal terms, are responding to the collapse of the current paradigm in a very ‘human’ way. (@RIB, this may be your new business model, as well…?)
The new economic paradigms need to function for humans, rather than robots. (I like robots; but they shouldn’t be running economies.)
“The traditional lending model was built around case-by-case judgment. Home buyers would apply for loans from their local bank, with which they often had an existing relationship.”
I think the place where the loss of this model is destroying our communities is in commercial lending. The huge dirty-dark secret out there is that there is no “small business” lending from the banks anymore. It’s just personal lending that gets spent on your business. SBA loans make you sign your personal assets. Why pay 12% for an SBA loan if you can borrow for 4% on your house? Your house is up against the loan either way.
But the huge loss is in the loss of ‘institutional memory’. A lending officer, with some history in the community, talking to an applicant about a prospective business in a particular location has some insight that is invaluable to the process. The officer knows the last three businesses that were in that location and what kind of obstacles they had. They know landlords and keep them in line by being less likely to approve loans for businesses in badly maintained buildings. They know the town and can shepherd projects through zoning and planning boards. They keep the process coherent.
Now it’s just a teller in your local location. Lending models in some computer in the Carolinas run a destructive swath through the country and our communities, with unsound projects creating empty buildings and unlikely projects sitting unfinished. The only people with the wherewithal to do all the analysis themselves and the lawyers to make it happen are large multinationals who build useless ‘boxes’ and huge parking lots, use predatory pricing to drive every small business within miles out of business and then leave town at their convenience leaving communities with huge, gaping holes and devoid of the small businesses that infuse them with life.
As another example of this overall phenomenon, about 4 years ago, I was looking for a car loan. My last car was in its death throes. I drive ’em till they can’t be driven any more.
I’d bought that car from an outfit that fixes wrecks. It’s a great deal if you keep the car till it’s done. You have a salvage title on it but unless you wreck it or try to sell it, it’s irrelevant. Anyway, that particular place typically dealt with one local credit union for loans. I didn’t have any particular preference so I said sure. I took out that loan for that car through them and made every payment at least on time, in fact, I paid it all off something like 5 or 6 months early.
Well, I drove the car several years after that and when it died, figured I’d go back to that credit union for a loan on another car. They knew me, right? They had experience with my honoring the contract.
Well, they told me that in 2002, some 4 years before I returned to seek a loan with them, that I’d made a mortgage payment late. Maybe I did. Maybe I didn’t. I think it was a matter of whether you went by the date I sent it out or the date they officially processed it. But that was 4 years previous to the time when we were talking and the credit union had first hand experience that I honored my debts.
The woman I dealt with told me they couldn’t give me a loan. I asked if my having paid them off early previously shouldn’t have some bearing on this. She acknowledged that I had and didn’t cite anything (credit score or any other late payments, because there weren’t any) else but told me that because of a perhaps late mortgage payment 4 years before, they could not offer me a loan. She wouldn’t budge off that no matter what.
Oh, I should have added that, at one point, she said something about it being part of a formula or something and that they weren’t allowed to go against it.
Yves, one critical reason that we have moved away from personal judgment in business decision-making is simply that we don’t trust personal judgment any more. One specific aspect of that, as you indicated, is in mortgage lending; but complaints over discriminatory treatment in mortgage lending, among other factors, have pushed us steadily away from a personal judgment-based model toward a statistical model. A person with sufficient experience will always know more about the myriad of factors involved in the likelihood of default than a computer program ever will; but a person can, and will, also include factors that we as a society do not want included in that decision-making.
There is a fundamental tension there that will not easily be resolved, so we will have to make a decision: what set of failings do we want to try and deal with on a regular basis, the deep systemic errors of computerized lending, or the personal failings of personalized lending?
I couldn’t agree more. As the use of computers has increased in accounting, I have seen less skepticism every year as to their output. If something is wrong with a model’s assumptions, fewer and fewer people are willing to challenge it until disaster occurs.
IA
I skimmed the article, but it doesn’t seem that he really offers an alternative. In my opinion, the use of econometrics is part of a larger problem, a sympton.
What would be interesting is to see if social-democratic countries like Germany, France, Sweden, etc. use econometric models in the same way and as much as the US and the UK do(Anglo-Saxon). I suspect that they don’t, and the fact that they have much lower poverty rates compared to the US and UK is not unrelated to this possiblity.
Okay, towards the end of the article, Bihde says:
“Yet if we are to preserve the primacy of human judgment, we must learn to harness and control these models, not submit to them.”
I submit that the models are useless and should be discarded altogether. Securitization should be banned, that is, the complex derivatives THAT NO ONE UNDERSTANDS should be gotten rid of completely as Taleb recommends.
The problem is political, that is, what is economic activity for?(as SKidelsky would say)
Over-reliance on simplistic models and theories, centralized decision-making, and the devaluation of local professional judgment–as well as Panglossian verbiage–afflicts much more than finance. It’s certainly true in education where there are to many upper management types who know everything, but understand nothing.
A driving factor is probably CYA-age. If you make decisions based on “universally accepted” formulae and principles rather than according to your judgment, you can’t be held responsible if it blows up. There is safety in numbers.
Second, and less negatively, in our large, mobile and anonymous society, we are increasingly dealing with people who we don’t know whether to trust (in their honesty or their professional judgment).
Most people don’t like complexity. Even when the world truly is complicated, they want to believe it is simple. Most of my experiences during the two plus decades I spent in investment banking convinced me that this is especially true among most so-called finance professionals.
I spent a lot of my career arguing for the importance of everyday bankers understanding how the numbers on their transactions worked. Management, with only a few exceptions, favored that bankers rely on black box software products (like the Intex system you describe) to structure and analyze their deals. The argument was simple: No risk of subjective individual error and standardized results. The fact that the black box could only take certain inputs (which even an idiot would have recognized were insufficient to describe all the relevant constraints for many typical transactions) was viewed as an asset rather than a draw back (sort of like Milton Friedman’s minimalist approach to economic modeling).
I had a personal bias in favor of understanding how particular deals actually worked since I spent most of my career building highly complex transaction specific models to structure the bond issues I was responsible for. That said, this became harder and harder to do over the last decade of my career as the emphasis on standardization and churning out product became ever greater (quantity routinely won out over quality). I will never forget that my putative manager’s primary criticism of my performance in my final yearend review (for 2004) consisted of his complaint that my tendency to use more than two paragraphs to describe the highly complex problems (that were frequently associated with my structuring complicated transactions) posed an unacceptable time burden for the managers responsible for reviewing my feedback.
I don’t have a problem with standardization in the situations you described. The utter failure of securitization, complex derivatives, etc. was due to the bad economic ideas they were based on, ideas like: markets are efficient and self-correcting which led to the dismantling of regulation among other things.
The so-called “complexity” of these deals is a cover really, like all the phony maths that disguise the conceptual impoverishment of mainstream academic economics.
Let me ask you: in all the “complex” models you made did you ever once try to include the possiblity of a prolonged slump, depression or economic collapse? My guess is no, since the economics you were using rule out such events a priori and forever.
This is a Vanilla Greed lament. Pernicious Greed has more fully corrupted and co-opted the old Vanilla Greed system. Boo hoo!
Broad centralized policy is essential for any democratic society. Its not a centralization issue, its a corruption of the centralization issue. Similarly, computers and computer models are only as good and useful as those who control them. When controlled by the ethically challenged they are like any other technical tool and become tools of deception.
The only remedial plan that will work is to regain control of the crooked government.
Deception is the strongest political force on the planet.
Wow. Perhaps you might want to change the name of this blog to “Financial Luddites”.
Remember this little gem:
http://www.timeshighereducation.co.uk/story.asp?storyCode=159331§ioncode=8
Skippy…the Gatling gun, atom/hydrogen bomb were in inception tools that were to end war…wtf happened?
So…we can layoff the bonaz boyz?
Two points about this article:
1. At the macro (investment banking) level, the same applies to rating agencies as to impersonal credit-scoring systems in retail lending: they encourage lenders to abandon their own judgments (aka due diligence) and rely instead on external, ‘impersonal’ systems to decide where to put their money. Rating agencies should be banished just as surely as credit-scoring algorithms.
2. I have had mortgages in two countries: over 25 years at floating rates (UK) and 10 years at a fixed rate (Belgium). I believe fixed rates were mandatory in Belgium at the time, leaving the interest rate risk with the lenders (who are professionals) rather than the borrowers (who are not).
Where there are floating-rate mortgages, a downturn in the housing market directly affects consumers’ finances, creating a severe downward multiplier effect on the rest of the economy. This happened disastrously in the UK in the early 1990s recession, and we are waiting for it to happen again (but UK house prices haven’t yet fallen far this time round).
Surely fixed-rate mortgages are to be preferred – though perhaps not over as long as 30 years! It is then up to the lenders – backstopped by proper regulators – to arrange their finances with all the caution that their clients deserve, and for which once upon a time bankers were well-known.
Quite so. Presumably the value of the borrower’s embedded option to refinance a fixed-rate mortgage is incorporated in the interest rate.
As you say, there’s an asymmetry in market knowledge and access to hedging vehicles, in the lender’s favor.
We should recall that our centrally-planned interest rates are administered by a bankster cartel called the Federal Reserve. Let the policy-making insiders protect themselves from the consequences of their own interventionism. Or else, ‘Share the seignorage, dudes!’
This is an interesting discussion.
The thing about securitization is that it never was about creating a viable business via modeling. It was always about selling an income stream to someone else. Which, in turn, IS always about modeling and salesmanship.
It’s the buyers who need better education. Investors who could have found an off-the-shelf version of Intex would probably have grown more cautious from running different scenarios and realizing there are ugly termination points with non-negligible probability of occuring. Just as “Sim-City” was used in some social study classes to demonstrate the impact of policy making, a similar product called “Sim-Finance” might have been a great tool for educating investors.
Although they are seldom specifically predictive, I don’t think models are the problem; it is asymmetry in power and available information that is the root problem. Like Alec Guinness in The Bridge Over the River Kway, educated professionals are so busy enjoying their intellectual craft that they fail to factor in the damage being done by dint of their captivity. That’s the big problem, the Centralized Economy problem.
No, the models are the immediate problem, partly because they claim to be predictive when they are not. Also, assymetries in information are also not really the problem(this is the behavioral economics idea isn’t it?)
There are countries(Canada, the European social-democracies) that did not experience financial crisis, while the Anglo-Saxon world did, why? THAT is the question or problem that needs to be investigated. In addition, not only did they for the most part not experience the financial crisis, their social outcomes: literacy, poverty rates, incarceration rates, infrastructure are much, much better then ours(the US and the UK).
Bihde is trying to have it both ways, he’s saying yes the models are useless, but we can fix them so that they don’t do more damage. This is not true, the models are completely useless and need to be gotten rid of.
I on the ball patriot raises a key point about the nature of potential future reform in the U.S. He argues “Broad centralized policy is essential for any democratic society. Its not a centralization issue, it a corrupton of the centralization issue…the only remedial plan that will work is to regain control of the crooked government.
In contrast,I would argue that the continued centralization of power over the past 130 years (in both the public and private sectors) resulting in the emergence and then alliance of Big Capital, Big Government, Big Bank (The Fed and the Treasury) and Big Interventionist Foreign Policy institutions, is the structual issue which must now be directly confronted by the American people.
Debureaucratization, decentralization, and the reimpowerment of individuals(a healthy subjectivity) and communities are the most important political issues of the day.
However these deeper structural issues will continue to remain incomprehensible when locked into Big Party (Republicans vs. Democrats) ideological blinders and narratives.
We do not have to settle for a centralized, bureaucratic democracy when our own historical traditions beckon us toward a more direct form of democratic participation.
Trouble is, it isn’t the bureaucratic that is the problem, it is the plutocratic, which runs the bureaucratic through fear.
Your living a fantasy that doesn’t exist. Nothing you say will help, but further lead toward the collapse of America.
Speaking as a Yank, I find it intriguing to keep a bit of attention on what’s going on in Britain at present.
The current Deputy PM, Nick Clegg, studied anthropology. (FWIW, Barak Obama’s mother was an anthropologist and he was later a community organizer, which would have been ‘applied anthropology’ in a restricted sense.)
Clegg is a ‘Liberal Democrat’, currently working in a coalition government with the British Conservatives. One of the Lib Dem claims is that to be effective, government has to stop trying to do the ‘top down’ nonsense that simply does not work.
Should you be interested, after the 12 minute mark in this video, you can get a bit of sense about how and why the Lib Dems are trying to focus on building ‘bottom up’, rather than ‘top down’ structures.
http://www.guardian.co.uk/politics/video/2009/jun/11/toynbee-test-nick-clegg
Personally, part of what I find engaging about the Toynbee interviews at the Guardian is the meatiness of the conversations, and the lack of ‘gotcha’ questions; I see nothing like this in US political interviews with electeds (with the possible exceptions of Bill Moyers or Rachel Maddow). Why, oh why, can’t the NYT or the US media do a set of interviews this meaty and free of outside distractions…? (sigh…)
This post reminded me of an NPR piece from a couple of year ago about how banks in Amish regions were faring well despite the crisis.
A Mortgage Banker In Amish Country
http://www.npr.org/templates/story/story.php?storyId=98156907
Johnson, lets take a brief look at the history of Big Capital and Big Government in the U.S. in order to more closely evaluate your assumption that “it isn’t the bureaucratic that is the problem, it is the plutocratic, which runs the bureaucratic through fear.”
Between 1900 and 1950 both the (public-sector) bureaucrats and the (private-sector) plutocrats (ie. Corporate Capital and the Federal State or Big Government and Big Capital)worked hand in glove in creating a vast administrative apparatus(which can be discussed in detail if you’re interested) that seved as a transitional strategy for the move from entrepreneural to monopoly capital.
This move was necessary in order to coordinate a “rational” concentration of capital, the technical reorganization of labor and the central management of social interaction within labor unions.
Many “plutocrats” recognized that such a transformation could only be worked out in partnership with the federal government, which was the only political institution with the powers to unite divesrse regions, classes and industries into a cooperative whole.
In doing so the State openly collaborated with the operations of the managerial structures of corporate capital. In addition to encouraging state intervention and regulation many corporate groups separated the functions of “managing” from “owning” and “planning” from “producing” which took control of corporate capital away from owners and control of productive skills away from workers–to entrust it to these new professional administrators and technicians.
Your conception of the nature of the structure of power in the U.S. may be too simplistic but this entire issue needs to be further discussed and debated.
Chalmers Johnson points out that the economics profession in the university in America, was commandeered for Cold War ideological purposes. Specifically, to be the intellectual front line defense against the Marxist Critique of capitalism. Additionally, as you can well see Yves, the only seat at the table for policy purposes are the economists. That is of course, after the lawyers and generals. None else need apply. Not sociologists, certainly not with their empirical wing spanning a century of critical thinking and valid theories about the social order. Daniel Ellsberg had a PhD from Harvard in economics, game theory and was hired by the economic department of the Rand Corp. for nuclear weapons system deployment. Something about mega-deaths. Obviously, even the untrained eye of the business school types can see the obvious. That economics has precious little to do with definitive, valid knowledge, that makes for a stable social order. Stalin like, yes, contra Stalin/Soviet. So by necessity, in lock step cold warrior fashion, the economists were one by one brought over to help in the free worlds fight against communism. They who develop econometric models also serve, even if the models are of no practical use for their stated purpose, it keeps the liberal minded and cosmopolitan type of thinkers in check, while we grind away at a ruthless and implacable enemy. But, that enemy is gone, vanquished. And in the process, we become what we hate. Stalin like. All too true. Now, The whole world is one big global market. Yea, we won. So, the economics profession is about as useful to the militarists, as our man in East Berlin. Does it come as no surprise that what you call a bubble, based on a wall of liquidity, I would call the best employment opportunity of my lifetime, and that of many of my peers. Not everyone needs to work in Lockheed or Boeing or General Dynamics. Some of us would like a job as secure and well paying as a defense contractor. But, the defense spending crowds out the rest of the economy outside of Eds and Meds. And high end finance apparently. As to why the Wall ST types get free rein, why their model does not have to work in an intellectually valid way as a social science,
is that they are, for want of a better word, the Jerry Falwell and 700 club of the material American Dream of getting and spending, hopefully millionaire status from Wall St to easy st. It is not just the Wall St firms preying on their customers like marks in a swindle, the whole society has moved into sales status, commissioned based preying one another. You certainly know the mortgage brokers would churn borrowers until there was no equity left. Every bank teller is trying to sell you, every floor person in even the humblest blockbuster video is poised to sign you up for something, a video game, candy, a super sized popcorn! We don’t manufacture a whole lot any more, but we sure do tele-market one another. Trying to sell the goods made elsewhere. Or now, try to collect the debt on whatever financed the purchases of the crap we sold to each other during the last boom time.