Wrong way econometricians

You Can’t Make This Stuff Up (TM)!
(now I wait for the royalties to roll in…)

Ha, I told you they were gonna try to blame albedo. Watch the coming demonization of the poor of this earth for their nasty particulates.
==========

I certainly know of economists, but can someone please tell me what an econometrician is? I notice as I type it the WordPress doesn’t seem to know what it is either.
Ross McKitrick has done statistical reviews of historical or model data, but what the hell are these guys doing making future temperature models? Is an econometrician a new form of a climate scientist?
It just gets funnier by the day! The funniest part is that ignorant media outlets pick this stuff up.

Marcel — What was the media response when they were notified of this?

™ (option+2)
Can’t trademark without the Trademark Trdemark ©

“masked much more of the warming of greenhouse gases than previously thought.”
Yea, yea, we know; it’s worse than we thought. It’s always worse than we thought.

Canada has their own Mark Jaccard, the author of the BC Carbon Tax… whose hero is Al Gore. No kidding http://www.vanmag.com/News_and_Features/Mark_Jaccard_Talks_Climate_Change
This interview falls into a series by author James Glave that we could call “hagiography of the Canadian climate activists”… LOL

“Yikes. This dataset is not to be used for the type of study performed by these econometricians. Never. Period. Don’t use it. Lies, damned lies, statistics and very sloppy science.”
Does this mean their work and conclusions are only ROBUST rather than VERY ROBUST??

The body of this mentions cru ts 2.1, while the answer refers to cru ts 2.0. Maybe not the same Data set?

What is the difference between CRU TS 2.0 and CRU TS 2.1?

“I certainly know of economists, but can someone please tell me what an econometrician is?”
I don’t know, either, but I’ve a sneaking suspicion that an econometrician is someone who is way smarter and better looking than you, no matter smart or good looking you are. 🙂
Seriously, though, it’s someone who applies mathematical and statistical techniques to economics (as if economics didn’t have enough trouble…)

Is 2.1 an extention of 2.0?
“”CRU produced the original high-resolution climate grids (CRU TS 1.0; New et al., 2000) and an update to 1998 (CRU TS 1.1). Mitchell et al (2004) revised these grids and extended them to the year 2000 (CRU TS 2.0). The CRU 2.1 data-set revises and extends previous CRU data-sets. The grids have been recalculated in the version 2.1 for 1901-2002 period, following a complete revision of the underlying station databases and using an improved method. CRU expects to update this dataset soon, with data up until 2005. CGIAR-CSI will provide an update when this becomes available””
http://csi.cgiar.org/cru/

“…can someone please tell me what an econometrician is?”
Someone who figures out how much it costs to wire a weather station?
🙂

For those of you confused about the whether the CRU TS 2.0 anthropogenic detection caveat is applicable to the CRU TS 2.1 dataset, please read this:
http://www.cru.uea.ac.uk/cru/data/hrg/timm/grid/CRU_TS_2_1_text.html#Guidance
Specifically, this part:
“The issues involved in using CRU TS 2.1 for time-series analysis are addressed more explicitly and fully; this guidance was originally given for CRU TS 2.0, but it applies equally to CRU TS 2.1. We recommend that all users who intend to examine climate change using this data-set should consider the issues carefully before beginning their work.”
The blurb links to the aformentioned CRU TS 2.0 anthropogenic detection caveat. So yes, it applies to both the 2.0 and 2.1 datasets equally.

Here is another critical error they made which completely undermines their entire case (independent of the CRU TS dataset issue), on page 23 they state:
“Since CO2 is well-mixed in the atmosphere (Forster et al, 2007, p. 138), we may assume that CO2 is the same for each weather station and hence we don’t require information at station level for CO2.”
Wrong. First of all, CO2 is NOT well-mixed in the atmosphere. Even NASA’s own chief scientist at JPL, Dr. Moustafa Chahine, said in a recent NASA press release that “contrary to prior assumptions, carbon dioxide is not well mixed in the troposphere”[1]. How much clearer of a signal do these guys need?
Second, how can anyone assume that CO2 levels are “the same” across weather stations? If that were true, why would it be necessary to locate CO2 monitoring stations in the most remote and inhospitable regions of the Earth?
1. http://www.jpl.nasa.gov/news/news.cfm?release=2009-196

JimAsh (16:48:17) :
™ (option+2)
Can’t trademark without the Trademark Trdemark ©
Ctrl-Shift-U-2122 -> ™
and to toss it in…
Ctrl-Shift-U-00A9 -> ©
What keystroke combo is “option 2”? Ah heck, where is the “option” button anyway?

In other Dutch news we learned that the former minister of milieu J. Cramer (old hag) paid half a million Euro’s to a spindoctor called “Maurits Groen” and his bureau “Milieu en Communicatie” (http://www.mgmc.nl/) in the running up to Copenhagen, basically she was handing out free money. My money that is.

kadaka,
And here I thought I maybe I was the only El Reg fan – Ars Technica is good too (lots of overlap), but the pro-AGW side of the coin.
Daniel H,
NASA really should have retracted that press release. Their “lumpy” CO2 distribution was less than 8 (maybe 6 if I recall the post and discussion here correctly) ppm in variance. We’re talking very minor variances (2% or less). Unfortunately hype seems to trump clarity with science these days… NASA should be better than that.

BTW – as much as everyone loves to hate economists, if used correctly econometrics can be very useful for finding relationships in data sets and analyzing their usefulness. Check out the post on mathematical analysis of CO2 that was posted a week or two back. Really intesting… to me at least
It is, in many ways, much more advanced than the methods used in climate science… but at the same time, a good statistician can make the results say whatever they want.
You have to start out with good data, your methods should be predetermined, and the results need to speak for themselves and not be spun. I’m not sure any of those apply to climate science.

I’m not sure if the Dutch study had used Jones instead of CRU TS 2.1, the findings would have been much different. They conclude that ignoring local dimming underestimates the greenhouse effect.
http://center.uvt.nl/staff/magnus/wip04.pdf

Tim C (17:34:46) :
“The “paper” is dated 1st September 2009, probably produced for the Copenhagen love-fest.”
Okay;
Copenhagen Snow-Fest ™

Nick Stokes (23:25:26) :
CRU is saying that their data TS 2.0 is unadjusted. “The grids are based on raw station data.”!
So what adjustments do you think they should have made?
Better ones than they have been making!!

Econometry is a technique; you can’t blame a technique for it’s wrong application. 95% percent of all papers are junk across all disciplines. I don’t blame computer science for the 95% junk papers about edge detection; what counts are the 5% good papers that form the basis of todays image processing technology. And they’re as good as gold.
Sturgeon’s law applies as usual, and it obviously also applies to newspapers.

Since mid-40ties, net global temperature increase is 0.3 deg C (per hadCRUT). Without UHI and data manipulation, it should be even less.
Based on WHAT did those pseudo-scientists forecast 22-times higher rate of temperature increase in next 40 years than up to now?? Not speaking about sober prediction by orthodox German climatologist Mojib Latif, who expects several decades of cooling, or at least stagnation of global temperatures.
Some people simply has no common sense.

But how can it be possible to model such a chaotic system as climate? Isn’t climate the ultimate chaotic system? Is it possible to model chaotic systems?
.
No .
“Chaotic system” and “model” are antinomic . Chaotic systems , despite the fact that they are strictly deterministic (most people think they are random what they definitely are not) , cannot be predicted beyond a finite rather short horizon . It is even their defining property .
.
Weather is chaotic therefore can’t be predicted and will never be predicted regardless the power of the computers beyond a horizon of a few days .
It is , per definition , also impossible to simulate them numerically beyond the horizon .
These are well known and mathematically proven properties of chaotic systems .
.
Now there exists a class of chaotic systems that have a property of ergodicity .
While they can’t be predicted like every other chaotic system , there exists a unique PDF (probability density function) that gives the distribution of the dynamical states in the phase space in the infinite time limit .
Such systems have a kind of statistical “predictability” over very long times .
Ergodic systems are mostly found only in temporal chaos (e.g systems with no spatial autocorrelation) as opposed to spatio-temporal chaos like clouds and fluid flows .
.
Now climate is a spatio-temporal chaotic system at all time scales and spatio temporal systems are generally NON ergodic .
Non ergodic systems can’t be predicted with any reasonable accuracy even statistically over long times .
.
So yes you are absolutely right : the Earth’s ocean-atmosphere-cryosphere dynamical system may be viewed as an example of an “ultimate” chaotic system .

Have a look at figure 2 in the paper: the highest temperature happens in 1990; 1998 is 2nd, 1999 3rd, and 1994 4th. That’s not the usual order.

Maybe it’s time for a real science of the climate to emerge. It should be called “climatonomy”.
After all, we have astrology versus the real thing: astronomy.
Looking back, there was a big clue in the name “climatology”.

Wren (22:53:26) :
As the authors of the paper say:
“What matters is whether small deviations from our assumptions will cause large or small changes in our conclusions.”
What matters is that they used a dataset specifically labeled “Do not use for climate change detection because you’ll get skewed results” and used it for — *sigh* — climate change detection.
Their assumptions are based on skewed results, and their conclusions are based on those assumptions.
It’s like me taking a topical medication for a skin rash — say, hydrocortisone cream — labeled “Not for internal use” and eating it, then concluding that, as a topical medication, it’s useless, because it didn’t improve the rash, and adding that the only thing that could affect my conclusion would be whether or not I chewed the medication before I swallowed it.

Arn Riewe (16:33:02) :
I certainly know of economists, but can someone please tell me what an econometrician is?
These are close cousins to the elite economic PHDs and MBAs who convinced the world that Liar (NINJA) mortgage loans were safe to package and leverage at up to 60 to one.

The study was actually lead by a good econometrician (Magnus, from UvT).
The data issues are indeed problematic, and it is quite awkward that they failed to notice this problem.
There is however, in my humble opinion, another potential problem with the study. They find an autoregressive term close to 1 (namely 0.91). Given that most authors conclude that temperature series are integrated of the first order, this should raise a red flag (i.e. the series contains a unit root, which, loosely put, implies that teh AR term is equal to 1, making regular inference invalid).
They do not even mention unit roots in their paper.
I do have to repeat that Magnus is a respected scientist, so all of this is highly awkward. However, I also have to add that I was a bit dismayed with how the paper started out:
“The Earth is getting warmer and much or all of this process is generally believed to be caused by humans. It is possible that humanity is about to face the most serious catastrophe since the Bubonic Plague in the fourteenth century killed 35 million people in Asia and half the population of Western Europe. Death from the plague was horrible, but swift. In The Decameron, Giovanni Boccaccio writes that victims often ‘ate lunch with their friends and dinner with their ancestors’. Global warming is not as swift, but its consequences could be no less horrible. There is much uncertainty about global warming. The purpose of this paper is to investigate the statistical evidence, using econometric panel data techniques.”
…. doesn’t sound as ‘impartial’ as an econometrician / statistician ought to be.
P.S. For those wondering: econometrics is the discipline of hypothesis testing using non-experimental data/observations. The issues it deals with are e.g. sample selectivity, unit roots in time series, clustered volatility, etc etc etc, and other non-experimental issues complicating (or even invalidating) statistical inference.
It was first developed by Gauss in the form of Ordinary Least Squares, for the purpose of calculating the parameters of planetary orbits. Calculating a linear ‘trend’ is in fact the most simple form of ‘econometrics’.
The field has grown exponentially since Jan Tinbergen (first Nobel laureate, economics, together with another econometrician Ragnar Frisch) basically set it in motion.
The term itself is quite misleading, because this is general ‘metrics’ we are talking about, rather than ‘statistics applying solely to economics’.
There was a post here on WUWT a few weeks ago, on a study by Beenstock and Reingewertz (two econometricians), who also apply (in their case different) statistical / econometric methods to evaluate the AGWH.
They however reject any long term relationship between CO2 and temperatures (and they take extreme care to ensure that the unit root issue I outlined above is dealt with).

Econometrics it’s stochastical !!!☺

fred wisse (06:20:08) :
It will always be the same , this is the wealthy supporting the mighty or the other way around , if you keep them dumb we shall keep them poor . Is this the name of the agw-game ?
REPLY:
Of course it is. CAGW is about funding a nondemocratic world government. The wealthy and powerful are not happy with democracies or national borders that interfere with trade. You will note the progressive shift to nondemocratic leadership in the last thirty years. A classic example is this from the United States FDA website:
International Harmonization: http://www.cfsan.fda.gov/~comm/int-laws.html
“The harmonization of laws, regulations and standards between and among trading partners requires intense, complex, time-consuming negotiations by CFSAN officials. Harmonization must simultaneously facilitate international trade and promote mutual understanding, while protecting national interests and establish a basis to resolve food issues on sound scientific evidence in an objective atmosphere. Failure to reach a consistent, harmonized set of laws, regulations and standards within the freetrade agreements and the World Trade Organization Agreements can result in considerable economic repercussions.
Participation in:
Codex Alimentarius
Cosmetics International Activities
International Organizations and Standard-Setting Bodies
International Office of Epizootics
International Plant Protection Convention
World Health Organization
Food and Agricultural Organization
Joint FAO/WHO Expert Committee on Food Additives (JECFA)
Joint Meeting on Pesticide Residues
Joint FAO/WHO Expert Committee on Microbiological Risk Assessments
Pan American Health Organization
Organization for Economic Cooperation and Development “
The FDA is now taking its orders, not from the people of the USA but from the United Nations and the World Trade Organization. For Europe the EU does similar things.
Unfortunately any reference to the move away from democracy towards governing by the wealth is called a “Conspiracy Theory”

Loved this bit in the “A1” response:
[…] the Jones temperature data-set […] is optimised for the reliable detection of anthropogenic trends.
That’s a corker.

I was under the impression that aerosols were on the decline…

Leif Svalgaard (16:57:42) :
This is on a coarser (5 degree) grid, but it is optimised for the reliable detection of anthropogenic trends.
If so, no wonder they find some.
Eureka! My thoughts exactly.

Wait a minute!
NickB. (07:04:48), we were discussing that at the Himalayan Hijinks thread. Now I have to cross-post to get the info [ref. kadaka (08:32:09)] over there.
*groan*

Tom Vonk (01.29.56)
But now I don’t understand about these datasets – if you can’t model climate, where do these datasets come in? They are still trying to forecast how a chaotic system will behave. I thought that was nonsense, so does the dataset make it any better?
I am going to predict how this leaf will blow around the garden, and I will use dataset A. No, I will use dataset B. ?? I am going to predict where the leaf will blow today depending on where it blew yesterday?

Bill Tuttle (04:06:52) :
Wren (22:53:26) :
As the authors of the paper say:
“What matters is whether small deviations from our assumptions will cause large or small changes in our conclusions.”
What matters is that they used a dataset specifically labeled “Do not use for climate change detection because you’ll get skewed results” and used it for — *sigh* — climate change detection.
Their assumptions are based on skewed results, and their conclusions are based on those assumptions.
It’s like me taking a topical medication for a skin rash — say, hydrocortisone cream — labeled “Not for internal use” and eating it, then concluding that, as a topical medication, it’s useless, because it didn’t improve the rash, and adding that the only thing that could affect my conclusion would be whether or not I chewed the medication before I swallowed it.
=====
No, it’s not quite like that, but I wouldn’t recommend eating hydrocortisone cream.
You should be able to use the Jones data set in the model.The question is had they used Jones instead of CRU TS 2.1, would the results be much different?

JonesII (07:29:36) :
“Gail Combs (06:53:51) :You are pointing to a real issue. Global Government it is already working,….”
Yes they have been sneaking it in little by little. The World Trade organization was the big step as was the European Union. Once you wise up to what is going on a lot of the “news” starts to make sense. Control Money (2008-2009 financial crisis), Energy (CAGW), Food (World Trade Organizations Agreement on Ag) and Land (UN control of “World Heritage Sites”/environmental laws) – there isn’t much freedom left for us serfs.
Since there is more than one “front” to the battle for our freedom it is a tough fight for an individual especially when you get labeled a “conspiracy nut” if you mention the different battle fronts.

NickB. (10:01:19) :
Oh crap – my apologies! I shouldn’t be allowed to interact with the world B.C. (before coffee)
Why I used to take a mug of coffee with me upstairs to the bedroom. It was cold, but it was there soon as I got up. Probably saved my life one or more times by keeping me from falling down the stairs while not exactly awake.
Side note, unheated coffee is great once you get used to it. Flavor stays good for a very long time, soon as the coffeemaker is done making a pot it gets switched right off. Saves a lot of energy. If you really need a warm cup, well then, microwave oven is right there, help yourself.

Wren (10:59:47) :
Bill Tuttle (04:06:52) :
You should be able to use the Jones data set in the model.The question is had they used Jones instead of CRU TS 2.1, would the results be much different?
Well, *I* couldn’t, because it wouldn’t stand up to peer review — I don’t have the background in either math or econometrics. But you’ve got an interesting question — just based on the cautionary against using CRU TS 2.1, I would intuit a definite “maybe”…

Daniel H (20:11:11) :
Here is another critical error they made which completely undermines their entire case (independent of the CRU TS dataset issue), on page 23 they state:
“Since CO2 is well-mixed in the atmosphere (Forster et al, 2007, p. 138), we may assume that CO2 is the same for each weather station and hence we don’t require information at station level for CO2.”
Wrong. First of all, CO2 is NOT well-mixed in the atmosphere. Even NASA’s own chief scientist at JPL, Dr. Moustafa Chahine, said in a recent NASA press release that “contrary to prior assumptions, carbon dioxide is not well mixed in the troposphere”[1]. How much clearer of a signal do these guys need?
Second, how can anyone assume that CO2 levels are “the same” across weather stations? If that were true, why would it be necessary to locate CO2 monitoring stations in the most remote and inhospitable regions of the Earth?
1. http://www.jpl.nasa.gov/news/news.cfm?release=2009-196

Depends of one’s definition of “well mixed”. Of course, that doesn’t mean that CO2 is everywhere on earth the same at any moment. That can only be if there were no sources and sinks at work. The largest disturbance is the growth and death of leaves over the seasons in the NH. That introduces a change in level of about +/- 8 ppmv at ground level in the NH, +/- 4 ppmv at 3,000 m and +/- 1 ppmv in the SH. For yearly averages, the differences are much smaller: a growing difference between the NH and SH (as 90% of human emissions are in the NH), now about 3 ppmv. Thus for yearly averages all stations on earth (and the satellites) are within 1% of each other’s level. Not bad for “well mixed”.
More stations are used, first as backup and second because of the seasonal variations. Nevertheless, in many cases only the data of one station (mauna Loa) is used for convenience, as that has the longest record…
For global warming, as far as the effect is measurable, the seasonal variability and the lag of the SH vs. the NH is of little effect, as the total growth is about 33% since the start of the industrial revolution.
Where the researchers were completely wrong, is the attribution of all warming of the past decades to CO2 and insolation. They completely ignore other natural influences, like the influence of the PDO and other ocean driven temperature influences. And they attribute the global dimming/brightening all on aerosols, where water vapour and cloud cover are a far more likely candidates for that.

kadaka (20:14:52) :
What keystroke combo is “option 2″? Ah heck, where is the “option” button anyway?

Second left from the spacebar—on a Mac, just after the Command key (sometimes called the ‘Apple’ key).
/Mr Lynn