Category: Aside

Braveheart & Rogaine

The Reinhart & Rogoff debt/growth paper continues to make a stir for it’s basic Excel errors. Colbert has the latest & funniest take on it.

Two things about this surprise me.

Confronted with obvious and irrefutable errors, the authors double down and admit nothing. They also downplay the significance of the results, ‘… we are very careful in all our papers to speak of “association” and not “causality” …’

But of course the (amplified) message, Debt/GDP>90%=doom, was taken causally in the policy world; see the multiple clips in the intro to the Colbert video. Politicians are nuts to accord one paper in a sea of macroeconomic thought so much weight, but I guess this was the one they liked.

EU ETS on the ropes

The EU declined backloading, a deferral of permit auctions that would have supported prices in the Emissions Trading System (ETS).

This is described imminent collapse to the system, threatening the achievement of emissions targets. Perhaps a political collapse is imminent – not my department – but the idea that low emissions prices threaten the system is a bit odd. The ETS price is a feedback mechanism. Low prices are a symptom, indicating that the marginal cost of meeting targets is extremely low. That should be a cause for celebration (except for traders).

For the umpteenth time, this shows the difficulty of running a system that invites wrangling over allocation and propagates noise from the economy into a market.

Meanwhile, carbon taxes grind away at their job.

On the usefulness of big models

Steven Wright’s “life size map” joke is a lot older than I thought:

On Exactitude in Science
Jorge Luis Borges, Collected Fictions, translated by Andrew Hurley.
…In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast Map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.
—Suarez Miranda,Viajes de varones prudentes, Libro IV,Cap. XLV, Lerida, 1658

It’s no less relevant to big models, though.

h/t Benjamin Blonder

Dynamic simulation the hard way

When Alan Turing was born 100 years ago, on June 23, 1912, a computer was not a thing—it was a person. Computers, most of whom were women, were hired to perform repetitive calculations for hours on end. The practice dated back to the 1750s, when Alexis-Claude ­Clairaut recruited two fellow astronomers to help him plot the orbit of Halley’s comet. ­Clairaut’s approach was to slice time into segments and, using Newton’s laws, calculate the changes to the comet’s position as it passed Jupiter and Saturn. The team worked for five months, repeating the process again and again as they slowly plotted the course of the celestial bodies.

Today we call this process dynamic simulation; Clairaut’s contemporaries called it an abomination. They desired a science of fundamental laws and beautiful equations, not tables and tables of numbers. Still, his team made a close prediction of the perihelion of Halley’s comet. Over the following century and a half, computational methods came to dominate astronomy and engineering.

From Turing’s Enduring Importance in Technology Review.

Minds are like parachutes, or are they dumpsters?

Open Minds has yet another post in a long series demolishing bizarre views of climate skeptics, particularly those from WattsUpWithThat. Several of the targets are nice violations of conservation laws and bathtub dynamics. For example, how can you believe that the ocean is the source of rising atmospheric CO2, when atmospheric CO2 increases by less than human emissions and ocean CO2 is also rising?

The alarming thing about this is that, if I squint and forget that I know anything about dynamics, some of the rubbish sounds like science. For example,

The prevailing paradigm simply does not make sense from a stochastic systems point of view – it is essentially self-refuting. A very low bandwidth system, such as it demands, would not be able to have maintained CO2 levels in a tight band during the pre-industrial era and then suddenly started accumulating our inputs. It would have been driven by random events into a random walk with dispersion increasing as the square root of time. I have been aware of this disconnect for some time. When I found the glaringly evident temperature to CO2 derivative relationship, I knew I had found proof. It just does not make any sense otherwise. Temperature drives atmospheric CO2, and human inputs are negligible. Case closed.

I suspect that a lot of people would have trouble distinguishing this foolishness from sense. In fact, it’s tough to precisely articulate what’s wrong with this statement, because it falls so far short of a runnable model specification. I also suspect that I would have trouble distinguishing similar foolishness from sense in some other field, say biochemistry, if I were unfamiliar with the content and jargon.

This reinforces my conviction that words are inadequate for discussing complex, quantitative problems. Verbal descriptions of dynamic mental models hide all kinds of inconsistencies and are generally impossible to reliably test and refute. If you don’t have a formal model, you’ve brought a knife, or maybe a banana, to a gunfight.

There are two remedies for this. We need more formal mathematical model literacy, and more humility about mental models and verbal arguments.

Computational gains in complex modeling

Interesting approaches to crowd simulation by abstracting agents to fluid fields (around 6:20), and model reduction for fast simulation of high-dimensional fluid problems (around 23:00) and realtime control (33:00):

I haven’t really digested the implications of this, but it’s interesting to consider what the implications might be for simulating lumpier systems, like traditional SD or economic models, where model reduction has not been very widespread, or for large-scale computing like climate models.

Politicians designing control systems, badly

We already have to fly in planes designed by lawyers (metaphorically speaking). Now House Republicans want to remove the windows and instruments from the cockpit. This is stupid. Really stupid. I’ve used ACS data on numerous public and private sector consulting engagements. I’m perfectly willing to pay for the data, but I seriously doubt that the private sector will supply a substitute. Anyway, some basic free data is needed so that all citizens can participate intelligently in democracy. Lacking that, we’ll have to fly blind. Say, what’s a mountain goat doing up here in a cloud bank?

Alternate perceptions of time

An interesting tidbit from Science:

Where Time Goes Up and Down

Dennis Normile

In Western cultures, the future lies ahead; the past is behind us. These notions are embedded in both gestures and spoken metaphors (looking forward to next year or back over the past year). A forward hand motion typically accompanies talk of the future; references to the past often bring a wave over the shoulder.

It is hard for most Westerners to conceive of other ways of conceptualizing time. But in 2006, Rafael Núñez, a cognitive scientist at the University of California, San Diego, reported that for the Aymara, an ethnic group of about 2 million people living in the Andean highlands, in both spoken and gestural terms, the future is unseen and conceived as being behind the speaker; the past, since it has been witnessed, is in front. They point behind themselves when discussing the future. And when talking about the past, Aymara gesture farther in front of them the more distant the event ….

At the Tokyo Evolutionary Linguistics Forum, Núñez presented another example of unusual thinking—and gesturing—about time: The Yupno people, who inhabit a remote valley in Papua New Guinea, think of time topographically. No matter which way a speaker is facing, he or she will gesture uphill when discussing the future and point downhill when talking about the past. …

I like the Aymara approach, with the future unseen behind the speaker. I bet there aren’t any Aymara economic models assuming perfect foresight as a model of behavior.

Where Time Goes Up and Down

  1. Dennis Normile