On a Clear Day You Can See the U.S. Dollar

Some choice quotes forwarded by Paul Brodsky at QB Asset Management on this fine Fed day:

“…the U.S. government has a technology, called a printing press (or, today, its electronic equivalent), that allows it to produce as many U.S. dollars as it wishes at essentially no cost. By increasing the number of U.S. dollars in circulation, or even by credibly threatening to do so, the U.S, government can also reduce the value of a dollar in terms of goods and services, which is equivalent to raising the prices in dollars of those goods and services. We conclude that, under a paper-money system, a determined government can always generate higher spending and hence positive inflation.”
-          Ben Bernanke, November 21, 2002

“Zimbabwe fell into a trap of a relentless casino economy. In that context, central banking had to become more of a national survival art and much less a doctrine of pushing and advancing dogmatic economic theories.”
-          Gideon Gono, Head of Zimbabwe Central bank, 2008

“Issue after issue of currency came; but no relief resulted save a momentary stimulus, which aggravated the disease. The most ingenious evasions of natural laws in finance which the most subtle theorists could contrive were tried – all in vain.”
-          Andrew Dickson White, writing in 1896 about the destruction of the French assignats of 1796.

“What is needed is credit. The credit that I propose to establish will be different in its nature from the kinds of credit now in general use.”
-          John Law, Comptroller General of France, 1720

Election Counter-Programming: Crowds, Clouds, Sheep and Beautiful Data

Thoughtful and fun MIT talk by Google’s Aaron Koblin about crowds, clouds, “data trails” and sheep. He is the creator of the famous flight patterns data visualization, as well as having created part of a Radiohead video.

Consider it election counter-programming: [-]

An example of visualizing TV channel engagement. Apparently Bloomberg viewers go to the Playboy channel in their off hours.

engagement.png

Misremembering Our Predictions Blinds Us to Past Forecasting Errors

An ever-deepening academic literature shows our utter inability to predict what will make us happy or sad. Add to that, however, new work which shows that we also don’t remember, ex post, what made us happy or sad — or if we even felt anything at all. It’s such magnificent obliviousness.

People aren’t very accurate at predicting how good or bad they’ll feel after an event — such as watching their team lose the big game or getting a flat-screen TV. But afterwards, they “misremember” what they predicted, revising their prognostications after the fact to match how they actually feel, according to new research.

…Across the studies, participants inaccurately predicted their feelings and wrongly recalled their predictions. Indeed, whether an event had been anticipated or dreaded, peoples’ revised predictions shifted toward how they actually felt. For example, Eagles fans said in advance they’d hate it if the Patriots won but afterward, they shrugged off the loss and said they always knew they’d be OK.

The results reveal a bias toward using current feelings to infer our earlier predictions. People don’t realize they made a mistake, so they don’t learn from that mistake — and keep making the same errors, said the researchers.

More here.

Source: ?Tom Meyvis, Rebecca K. Ratner, Jonathan Levav. Why Don’t We Learn to Accurately Forecast Feelings? How Misremembering Our Predictions Blinds Us to Past Forecasting Errors. Journal of Experimental Psychology: General, 2010; 139 (4): 579-589 DOI: 10.1037/a0020285

True or False: Consumer Wealth isn’t Tied to Homes, So STFU

Entertainingly nuts case on household wealth made by Tobias Levkovich of Citi in a new report. He argues that we’ve exaggerated the connection between consumer wealth and home values, that it’s “only” around 15.4%, so we should just STFU about the subject, or least not get so worked up.

Here is the chart with which Levkovich tries to make his case: [-]

wealth.png

Rather than me saying why I think this is a bullshit argument, I’ll leave it as an exercise for you fine folks. Anyone want to explain to Tobias why he’s adrift?

Quote of the Day: Sampling and Statistical Significance

Love this:

“Next time someone tells you they don’t believe a small sample poll can possibly tell you anything, just say to them ‘OK, then. Next time you have to have a blood test, why don’t you ask them to take the whole lot?’”

– British opinion pollster Nick Moon, in Significance, March 2010 (via Chance)

China’s Housing Bubble Flips the Preference for Boys

From the FT, an unintended consequence of China’s housing bubble:

But the conventional wisdom – that China is a land of unwanted girls, many of them sent overseas for adoption – is being turned on its head as urbanisation increases thecost of raising male heirs and erodes the advantage of having sons to work the fields and support parents in their dotage.

According to a recent World Bank report, the gender imbalance favouring boys peaked in Beijing and a few provinces in 1995 and has fallen since then. Additional provinces saw a similar trend in 2000, raising expectations that the country as a whole may have turned a corner with regard to female offspring.

More here.

The Poor are Sharks, Part XXIV

From a new Credit Suisse report on deleveraging:

… between 2002 and 2005 the correlation between [U.S.] zip code level house prices and local incomes actually went negative. That means if in a neighborhood was getting relatively poorer, then house prices were rising. And if it was getting richer, house prices were falling.

Venture Capital, Slow Change, and the Real World of Technology

Some typically savvy comments from my friend Tom Baruch of CMEA. As much as politicians and promoters shout about innovation, and as much as we go on and on endlessly about the wonders of entrepreneurs, the reality is that in many important areas — like energy — real change takes a long time, making our investing orthodoxies non-viable. [-]

In venture capital, it’s really a simple equation—it’s about the mathematics of compound interest. We talk about Moore’s Law, and we apply it to genomics, we apply it to transistor density on semiconductor chips, we apply it to speed and power and memory and calculations per second, but that’s really only one part of it. I believe Moore’s Law has really accounted for the creation of the whole venture capital business due to the fact that it can create exponential change. If you look at every major innovation in energy since the mid-1800s, historically these have been preceded by a major innovation in materials science. The problem is that it generally takes 20 to 50 years before they’re successfully commercialized. Compound interest is also exponential, and there is no market big enough to create an acceptable return when you’re taking 20 to 50 years to make a difference. That’s the bottom line. I don’t hear many people talking about that—maybe it’s the elephant in the room.

From Forbes/Wolfe Emerging Tech Report.

The Innovation Totem

I am tired of all the exhortatory calls for more innovation. Not that I’m against change — because I’m not — but the rote calls from all directions feel increasingly reflexive. It is superstitious, blinded by recent history (while longer spans of time show that innovation can equally involve giant steps backward that throw society into millennial disarray), and self-congratulatory. It exhausts and frustrates me in its squalling infantilism.

Gillian Tett makes a similar point at the FT:

But, as anthropologists have loved to point out, since the days of Claude Lévi-Strauss onwards, totems tend to be most potent when they are ambiguous enough to conceal contradictions. That innovation totem is no exception.

More here.

Credit Default Swaps: Not All Noise

New paper from FRB Atlanta pointing out the fairly obvious: While sovereign credit default swaps are traders’ tinker toys, they aren’t completely divorced from changes in the underlying riskiness of countries debt. Good to see the case being made, however.

Spreads on credit default swaps for some countries’ sovereign debt have increased recently. Given the terms of CDS contracts, this increase in the spreads can be interpreted as a reflection of heightened concern about countries having difficulty making the promised payments. On the other hand, the increase in spreads could simply reflect mindless speculation on these countries’ debt.

A review of the Irish CDS spread indicates that CDS spreads have been reacting to news—about both Ireland and the European Union. Large changes in the Irish spread in late 2008 and in early 2009 reflected Irish developments, but later changes before September 2010 were associated with European Union developments. The Irish spread has been sensitive to news concerning Ireland and to news concerning Greece and the European Union’s responses to the Greek government’s difficulties.