Faking fitness

Geoffrey Miller wonders why we haven’t met aliens. I think his proposed answer has a lot to do with the state of the world and why it’s hard to sell good modeling.

I don’t know why this 2006 Seed article bubbled to the top of my reader, but here’s an excerpt:

The story goes like this: Sometime in the 1940s, Enrico Fermi was talking about the possibility of extraterrestrial intelligence with some other physicists. … Fermi listened patiently, then asked, simply, “So, where is everybody?” That is, if extraterrestrial intelligence is common, why haven’t we met any bright aliens yet? This conundrum became known as Fermi’s Paradox.

It looks, then, as if we can answer Fermi in two ways. Perhaps our current science over-estimates the likelihood of extraterrestrial intelligence evolving. Or, perhaps evolved technical intelligence has some deep tendency to be self-limiting, even self-exterminating. …

I suggest a different, even darker solution to the Paradox. Basically, I think the aliens don’t blow themselves up; they just get addicted to computer games. They forget to send radio signals or colonize space because they’re too busy with runaway consumerism and virtual-reality narcissism. …

The fundamental problem is that an evolved mind must pay attention to indirect cues of biological fitness, rather than tracking fitness itself. This was a key insight of evolutionary psychology in the early 1990s; although evolution favors brains that tend to maximize fitness (as measured by numbers of great-grandkids), no brain has capacity enough to do so under every possible circumstance. … As a result, brains must evolve short-cuts: fitness-promoting tricks, cons, recipes and heuristics that work, on average, under ancestrally normal conditions.

The result is that we don’t seek reproductive success directly; we seek tasty foods that have tended to promote survival, and luscious mates who have tended to produce bright, healthy babies. … Technology is fairly good at controlling external reality to promote real biological fitness, but it’s even better at delivering fake fitness—subjective cues of survival and reproduction without the real-world effects.

Fitness-faking technology tends to evolve much faster than our psychological resistance to it.

… I suspect that a certain period of fitness-faking narcissism is inevitable after any intelligent life evolves. This is the Great Temptation for any technological species—to shape their subjective reality to provide the cues of survival and reproductive success without the substance. Most bright alien species probably go extinct gradually, allocating more time and resources to their pleasures, and less to their children. They eventually die out when the game behind all games—the Game of Life—says “Game Over; you are out of lives and you forgot to reproduce.”

I think the shorter version might be,

The secret of life is honesty and fair dealing… if you can fake that, you’ve got it made. – Attributed to Groucho Marx

The general problem for corporations and countries is that there’s a big problem attributing success to individuals. People rise in power, prestige and wealth by creating the impression of fitness, rather than creating any actual fitness, as long as there are large stocks that separate action and result in time and space and causality remains unclear. That means that there are two paths to oblivion. Miller’s descent into a self-referential virtual reality could be one. More likely, I think, is sinking into a self-deluded reality that erodes key resource stocks, until catastrophe follows – nukes optional.

The antidote for the attribution problem is good predictive modeling. The trouble is, the truth isn’t selling very well. I suspect that’s partly because we have less of it than we typically think. More importantly, though, leaders who succeeded on BS and propaganda are threatened by real predictive power. The ultimate challenge for humanity, then, is to figure out how to make insight about complex systems evolutionarily successful.

Dynamics of financial guarantee programs

Ever since the housing market fell apart, I’ve been meaning to write about some excellent work on federal financial guarantee programs, by colleagues Jim Hines (of TUI fame) and Jim Thompson.

Designing Programs that Work.

This document is part of a series reporting on a study of tederal financial guarantee programs. The study is concerned with how to design future guarantee programs so that they will be more robust, less prone to problems. Our focus has been on internal (that is. endogenous) weaknesses that might inadvertently be designed into new programs. Such weaknesses may be described in terms of causal loops. Consequently, the study is concerned with (a) identifying the causal loops that can give rise to problematic behavior patterns over time, and (b) considering how those loops might be better controlled.

Their research dates back to 1993, when I was a naive first-year PhD student, but it’s not a bit dated. Rather, it’s prescient. It considers a series of design issues that arise with the creation of government-backed entities (GBEs). From today’s perspective, many of the features identified were the seeds of the current crisis. Jim^2 identify a number of structural innovations that control the undesirable behaviors of the system. It’s evident that many of these were not implemented, and from what I can see won’t be this time around either.

There’s a sophisticated model beneath all of this work, but the presentation is a nice example of a nontechnical narrative. The story, in text and pictures, is compelling because the modeling provided internal consistency and insights that would not have been available through debate or navel rumination alone.

I don’t have time to comment too deeply, so I’ll just provide some juicy excerpts, and you can read the report for details:

The profit-lending-default spiral

The situation described here is one in which an intended corrective process is weakened or reversed by an unintended self-reinforcing process. The corrective process is one in which inadequate profits are corrected by rising income on an increasing portfolio. The unintended self-reinforcing process is one in which inadequate profits are met with reduced credit standards which cause higher defaults and a further deterioration in profits. Because the fee and interest income lrom a loan begins to be received immediately, it may appear at first that the corrective process dominates, even if the self-reinforcing is actually dominant. Managers or regulators initially may be encouraged by the results of credit loosening and portfolio building, only to be surprised later by a rising tide of bad news.

Figure 7 - profit-lending-default spiral

As is typical, some well-intentioned policies that could mitigate the problem behavior have unpleasant side-effects. For example, adding risk-based premiums for guarantees worsens the short-term pressure on profits when standards erode, creating a positive loop that could further drive erosion.

Continue reading “Dynamics of financial guarantee programs”

The RPX is up

While the Case-Shiller index is down and the conventional wisdom suggests that housing prices will continue to fall, the RPX composite is up for the first time since 2007. The year-on-year ratio hit bottom in Feb 09. The RPX has a lot less lag than the CSI, but also a seasonal signal, so this could merely mean that seasonally adjusted prices are just falling more slowly, but it would be nice if it reflected green shoots. I’m not holding my breath though.

The Growth Bubble

I caught up with my email just after my last post, which questioned the role of the real economy in the current financial crisis. I found this in my inbox, by Thomas Friedman, currently the most-emailed article in the NYT:

Let’s today step out of the normal boundaries of analysis of our economic crisis and ask a radical question: What if the crisis of 2008 represents something much more fundamental than a deep recession? What if it’s telling us that the whole growth model we created over the last 50 years is simply unsustainable economically and ecologically and that 2008 was when we hit the wall ’” when Mother Nature and the market both said: ‘No more.’

Certainly there are some parallels between the housing bubble and environment/growth issues. You have your eternal growth enthusiasts with plausible-sounding theories, cheered on by people in industry who stand to profit.

There’s plenty of speculation about the problem ahead of time:
Google news timeline - housing bubble

Google news timeline – housing bubble

People in authority doubt that there’s a problem, and envision a soft landing. In any case, nobody does anything about it.

Sound familiar so far?

However, I think it’s a bit of a leap to attribute our current mess to unsustainability in the real economy. For one thing, in hindsight, it’s clear that we weren’t overshooting natural carrying capacity in 1929, so it’s clearly possible to have a depression without an underlying resource problem. For another, we had ridiculously high commodity prices, but not many other direct impacts of environmental catastrophe (other than all the ones that have been slowly worsening for decades). My guess is that environmental overshoot has a lot longer time constant than housing or tech stock markets, both on the way up and the way down, so overshoot will evolve in more gradual and diverse ways at first. I think at best you can say that detecting the role of unsustainable resource management is like the tropical storm attribution problem. There are good theoretical reasons to think that higher sea surface temperatures contribute to tropical storm intensity, but there’s little hope of pinning Katrina on global warming specifically.

Personally, I think it’s possible that EIA is right, and peak oil is a little further down the road. With a little luck, asset prices might stabilize, and we could get another run of growth, at least from the perspective of those who benefit most from globalization. If so, will we learn from this bubble, and take corrective action before the next? I hope so.

I think the most important lesson could be the ending of the housing bubble, as we know it so far. It’s not a soft landing; positive feedbacks have taken over, as with a spark in a dry forest. That seems like a really good reason to step back and think, not just how to save big banks, but how to turn our current situation into a storm of creative destruction that mitigates the bigger one coming.

What about the real economy?

I sort of follow a bunch of economics blogs. Naturally they’re all very much preoccupied with the financial crisis. There’s a lot of debate about Keynesian multipliers, whether the stimulus will work, liquidity traps, bursting bubbles, and the like. If you step back, it appears to be a conversation about how to use fiscal and monetary policy to halt a vicious cycle of declining expectations fueled by financial instruments no one really understands – essentially an attempt to keep the perceived economy from dragging down the real economy (as it is clearly now doing). The implicit assumption often seems to be that, if we could only untangle the current mess, the economy would return to its steady state growth path.

What I find interesting is that there’s little mention of what might have been wrong in the real economy to begin with, and its role in the current crisis. Clearly the last decade was a time of disequilibrium, not just in the price of risk, but in the real capital investments and consumption patterns that flowed from it. My working hypothesis is that we were living in a lala land of overconsumption, funded by deficits, sovereign wealth funds, resource drawdown, and failure to invest in our own future. In that case, the question for the real economy is, how much does consumption have to fall to bring things back into balance? My WAG is 15% – which implies a heck of a lot of reallocation of activity in the real economy. What does that look like? Could we see it through the fog of knock-on effects that we’re now experiencing? Is there something we could be doing, on top of fiscal and monetary policy, to ease the transition?

Killer Models?

I was just looking up Archimedean copulas, and stumbled across a bunch of articles blaming the Gaussian copula for the crash, like this interesting one at Wired.

Getting into trouble by ignoring covariance actually has a long and glorious history. Want to make your complex device look super reliable? Decompose it into a zillion parts, then assess their collective probability of failure without regard for collateral damage and other feedbacks that correlate the failure of one part with another. Just don’t check for leaks with a candle afterwards.

Still, blaming copulas, or any other model, for the financial crisis strikes me as a lot like blaming a telephone pole for your car crash. Never mind that you were speeding, drunk, and talking on the phone. It’s not the models, but a general predisposition to ignore systemic risk that brought down the system.

SD on Long Waves, Boom & Bust

Two relevant conversations from the SD email list archive:

Where are we in the long wave?

Bill Harris asks, in 2003,

… should a reasonable person think we are now in the down side of a long wave? That the tough economic times we’ve seen for the past few years will need years to work through, as levels adjust? That simple, short-term economic fixes wont work as they may have in the past? That the concerns we’ve heard about deflation should be seen in a longer context of an entire cycle, not as an isolated event to be overcome? Is there a commonly accepted date for the start of this decline?

Was Bill 5 years ahead of schedule?

Preventing the next boom and bust

Kim Warren asks, in 2001,

This is a puzzle – we take a large fraction of the very brightest and best educated people in the world, put them through 2 years of further intensive education in how business, finance and economics are supposed to work, set them to work in big consulting firms, VCs, and investment banks, pay them highly and supervise them with very experienced and equally bright managers. Yet still we manage to invent quite implausible business ideas, project unsustainable earnings and market performance, and divert huge sums of money and talented people from useful activity into a collective fantasy. Some important questions remain unanswered, like who they are, what they did, how they got away with it, and why the rest of us meekly went along with them? So the challenge to SDers in business is … where is the next bubble coming from, what will it look like, and how can we stop it?

Clearly this is one nut we haven’t cracked.

Can Montana Escape Recession Ravages?

The answer is evidently now “no”, but until recently the UofM’s Bureau of Business and Economic Research director Patrick Barkey thought so:

“As early as last summer we still thought Montana would escape this recession,” he said. “We knew the national economic climate was uncertain, but Montana had been doing pretty well in the previous two recessions. We now know this is a global recession, and it is a more severe recession, and it’s a recession that’s not going to leave Montana unscathed.”

Indeed, things aren’t as bad here as they are in a lot of other places – yet. Compare our housing prices to Florida’s:

MT vs FL house price indexes

On the other hand, our overall economic situation shows a bigger hit than some places with hard-hit housing markets. Here’s the Fed’s coincident index vs. California:

MT coincident index of economic activity

As one would expect, the construction and resource sectors are particularly hard hit by the double-whammy of housing bubble and commodity price collapse. In spite of home prices that seem to have held steady so far, new home construction has fallen dramatically:

MT housing

Interestingly, that hasn’t hit construction employment as hard as one would expect. Mining and resources employment has taken a similar hit, though you can hardly see it here because the industry is comparatively small (so why is its influence on MT politics comparatively large?).

MT construction & mining employment

So, where’s the bottom? For metro home prices nationwide, futures markets think it’s 10 to 20% below today, some time around the end of 2010. If the recession turns into a depression, that’s probably too rosy, and it’s hard to see how Montana could escape the contagion. But the impact will certainly vary regionally. The answer for Montana likely depends a lot on two factors: how bubbly was our housing market, and how recession-resistant is our mix of economic activity?

On the first point, here’s the Montana housing market (black diamonds), compared to the other 49 states and DC:

State home price index vs 2000

Prices above are normalized to 2000 levels, using the OFHEO index of conforming loan sales (which is not entirely representative – read on). At the end of 2003, Montana ranked 20th in appreciation from 2000. At the end of 2008, MT was 8th. Does the rise mean that we’re holding strong on fundamentals while others collapse? Or just that we’re a bunch of hicks, last to hear that the party’s over? Hard to say.

It’s perhaps a little easier to separate fundamentals from enthusiasm by looking at prices in absolute terms. Here, I’ve used the Census Bureau’s 2000 median home prices to translate the OFHEO index into $ terms:

State median home prices

Among its western region peers, a few other large states, and random states I like, Montana starts to look like a relative bargain still. The real question then is whether demographic trends (latte cowboys like me moving in) can buoy the market against an outgoing tide. I suspect that we’ll fare reasonably well in the long run, but suffer a significant undershoot in the near term.

The OFHEO indices above are a little puzzling, in that so many states seem to be just now, or not yet, peaking. For comparison, here are the 20 metro areas in the CSI index (lines), together with Gallatin County’s median prices (bars):

Gallatin County & CSI metro home prices

These more representative indices still show Montana holding up comparatively well, but with Gallatin County peaking in 2006. I suspect that the OFHEO index is a biased picture of the wider market, due to its exclusion of nonconforming loans, and that this is a truer picture.

Real Estate Roundup

Ira Artman takes a look at residential real estate price indices – S&P/Case-Shiller (CSI), OFHEO, and RPX. The RPX comes out on top, for (marginally) better correlation with foreclosures and, more importantly, a much shorter reporting lag than CSI. This is a cause for minor rejoicing, as we at Ventana helped create the RPX and are affiliated with Radar Logic. Perhaps more importantly, rumor has it that there’s more trading volume on RPX.

In spite of the lag it introduces, the CSI repeat sales regression is apparently sexy to economists. Calculated Risk has been using it to follow developments in prices and price/rent ratios. Econbrowser today looks at the market bottom, as predicted by CSI forward contracts on CME. You can find similar forward curves in Radar’s monthly analysis. As of today, both RPX and CSI futures put the bottom of the market in Nov/Dec 2010, another 15% below current prices. Interestingly, the RPX forward curve looks a little more pessimistic than CSI – an arbitrage opportunity, if you can find the liquidity.

Artman notes that somehow the Fed, in its flow of funds reporting, missed most of the housing decline until after the election.