From the Institute for Energy Research:
…
It is this second class of models, the economic/climate hybrids called Integrated Assessment Models, that Pindyck discusses. Pindyck’s paper is titled, “Climate Change Policy: What Do the Models Tell Us?” Here is his shocking answer, contained in the abstract:
Very little. A plethora of integrated assessment models (IAMs) have been constructed and used to estimate the social cost of carbon (SCC) and evaluate alternative abatement policies. These models have crucial flaws that make them close to useless as tools for policy analysis: certain inputs (e.g. the discount rate) are arbitrary, but have huge effects on the SCC estimates the models produce; the models’ descriptions of the impact of climate change are completely ad hoc, with no theoretical or empirical foundation; and the models can tell us nothing about the most important driver of the SCC, the possibility of a catastrophic climate outcome. IAM-based analyses of climate policy create a perception of knowledge and precision, but that perception is illusory and misleading. [Bold added.]
For those unfamiliar with academic prose, such inflammatory language is almost unheard-of, particularly for a politically sensitive topic such as climate change economics. Pindyck is here reaching the exact same conclusion that I gave in my recent testimony before Senator Barbara Boxer and other members of the Senate Environmental and Public Works Committee: The computer models used by the Obama Administration’s Working Group to estimate the so-called “social cost of carbon” should not be the basis of federal policy.
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“Any Result One Desires”
In my testimony, I said the “economist can produce just about any estimate of the social cost of carbon desired.” Pindyck reaches the same conclusion in his paper when he writes:
And here we see a major problem with IAM-based climate policy analysis: The modeler has a great deal of freedom in choosing functional forms, parameter values, and other inputs, and different choices can give wildly different estimates of the SCC and the optimal amount of abatement. You might think that some input choices are more reasonable or defensible than others, but no, “reasonable” is very much in the eye of the modeler. Thus these models can be used to obtain almost any result one desires. [Pindyck p. 5, bold added.]
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Full story: http://www.instituteforenergyresearch.org/2013/08/12/scathing-mit-paper-blasts-obamas-climate-models/
The paper is here:
Click to access Climate-Change-Policy-What-Do-the-Models-Tell-Us.pdf
Most companies require a business plan before big money is invested in development, manufacturing, marketing and distribution. People who write business plans know well that …
1. Profit projections are exquisitely sensitive to cost of capital (interest rate) and its relative the discount rate. Neither is knowable in advance.
2. Expected sales volumes are best described as informed guesses with fancy graphs attached.
So projected sales are “very much in the eye of the modeler” which is why so many new products fail and should be a lesson to those trying to spend our grandchildren’s money to prevent catastrophic global warming.
This from HBR …
As partners in a firm that specializes in product launches, we regularly get calls from entrepreneurs and brand managers seeking help with their “revolutionary” products. After listening politely, we ask about the research supporting their claims. The classic response? “We haven’t done the research yet, but we know anecdotally that it works and is totally safe.” We’ve been fielding these calls for so long that we can often tell from one conversation whether the launch will succeed.
http://hbr.org/2011/04/why-most-product-launches-fail/ar/1
“Saviour Machine” lyrics by David Bowie:
President Joe once had a dream
The world held his hand, gave their pledge
So he told them his scheme for a Saviour Machine
They called it the Prayer, its answer was law
Its logic stopped war, gave them food
How they adored till it cried in its boredom
‘Please don’t believe in me, please disagree with me
Life is too easy, a plague seems quite feasible now
or maybe a war, or I may kill you all
Don’t let me stay, don’t let me stay
My logic says burn so send me away
Your minds are too green, I despise all I’ve seen
You can’t stake your lives on a Saviour Machine
Mark XR says:
August 14, 2013 at 3:10 pm
“I guess one could read the paper …”
Congratulations, Mark, Pindyck got you to take the bait and swallow it whole! Don’t you wonder why there was no semblance of the content of the last paragraph of his paper – which you quoted – in the Abstract?
But I thought that’s why they are used. :-p
@ur momisugly Eliza says.
In Australia, the alternate to a Rudd Govt., will persue emission cuts just as avidly, but not with a CO2 tax but with money hand outs in exchange for emission reductions. It will cost us just as much or more. Meanwhile, funding that Labor has been providing for habitat restoration and protection and important ecosystem management, will be cut by a conservative Govt. We have seen this already in Qld., where that and important social services were cut. Don’t let the politics obscure what is real.
I like that simple AC controller. More energy would be saved if I manually controlled the heating and cooling in my house than trying to program the non-intuitive complex array of buttons and readouts that I currently have. The digital controls are constantly getting stuck in some weird continuously heating or cooling mode without shutting down as programmed. The same is true in my remodeled office. Windows that could be opened and closed by hand, were removed, and now everyone swelters or freezes according to some digital presets.
“One can think of a GHG abatement policy as a form of insurance… .”
[Mark XR quoting from above paper at 3:10PM today]
Except, this “insurance” would:
1. Insure against loss that is ephemeral at best.
2. Raise the cost of doing business (of the U.S. economy as a whole) to the point that it would create a net loss.
[Note: This is the prima facie case, the burden of proof is, thus, on the CAGWers to refute it by proving their policies do no harm to the economy]
3. Any “government tax refunds” or “government subsidies” are a joke. The “government” is broke — to the tune of around $17 trillion, so, where will they get the money?………. BINGO!
Result: No more need for insurance. Whoopee.
TAXES KILL JOBS — JUST SAY NO.
“these models can be used to obtain almost any result one desires…The computer models used by the Obama Administration’s Working Group to estimate the so-called “social cost of carbon” should not be the basis of federal policy.”
Do you think Obama cares? ITTS (Its the tax stupid)
Tax his land, tax his wage,
Tax his bed in which he lays.
Tax his tractor, tax his mule,
Teach him taxes are the rule.
Tax his cow, tax his goat,
Tax his pants, tax his coat.
Tax his ties, tax his shirts,
Tax his work, tax his dirt.
Tax his chew, tax his smoke,
Teach him taxes are no joke.
Tax his car, tax his grass,
Tax the roads he must pass.
Tax his food, tax his drink,
Tax him if he tries to think.
Tax his sodas, tax his beers,
If he cries, tax his tears.
Tax his water, tax his air
Tax his donkey, tax his mare
Tax his hammer and his nail
Tax him if he dares exhale
Tax his bills, tax his gas,
Tax his notes, tax his cash.
Tax him good and let him know
That after taxes, he has no dough.
If he hollers, tax him more,
Tax him until he’s good and sore.
Tax his coffin, tax his grave,
Tax the sod in which he lays.
Put these words upon his tomb,
“Taxes drove me to my doom!”
And when he’s gone, we won’t relax,
We’ll still be after the inheritance tax.
One reason that us meteorologists are so skeptical of global climate models is that we use models every day.
The so called “butterfly effect” “Does the flap of a butterfly’s wing in Brazil set off a tornado in Texas”.
What this means is that slight changes in initial conditions can amplify greatly with time and turn into horrendous errors.
Any operational meteorologist with experience has busted hundreds of forecasts…….even the best. We are limited by weather models to use for guidance. Forecasts going out several days obviously show more skill but since there is a need for weather forecasts going out as far as any skill can be shown, we try to push the time frame out to 2 weeks and beyond in some cases.
Models like the GFS that go out to 384 hours, every 6 hours are what we use to analyze pressure, moisture, temperature and other key elements going out during that period.
So lets say we have one of the best meteorologists forecasting out 2 weeks, every single day starting on January 1st 1990. How many forecasts will he or others like him/her have made starting out on that date and ending 25 years later? This includes forecasts made and also, with the 2 week time frame each time, a skill level that can be assessed by comparing with actual results and an extremely high confidence level of skill because of the many forecasts(of both the forecaster and the models).
25 years X 365 forecasts/year – 14 days(the results of his last 14 forecasts will not be complete)==9,111 forecasts with verified results using computer weather models.
Let’s take a climate scientist who in that same year, 1990 uses global climate models to forecast the next 50 years(which is a time frame that they are using to predict our future climate and base governmental policies on). In 25 years, which is 2015, how many of his forecasts and the model forecasts will have been completed in order to ascertain a skill level?
Answer-0(zero) In fact, their first forecast will have only be halfway from the end point in 2015.
This is the entire problem and complete detachment from reality that climate scientists are having with the every increasing divergence between their models and the real world.
There are clearly many differences in the equations and physics between weather and climate models but the point is, they are both models and the meteorologist has had 9,111 opportunities to understand the flaws of his type of model(some of which are inherent in most models, including climate models) and the climate scientist is still waiting around to get a full assessment of his first model/forecast score.
The global climate models have already busted badly. This has been blatantly obvious for quite some time to those comparing with the real world. Climate scientists seem to be the last to see it.
Ego, bias, agenda and lack of recognizing the “butterfly effect” in climate modeling when you pick the wrong math equations to represent the physics and are off by a little are some reasons for this.
I knew some meteorologists who were slow to change their forecast when it was falling apart, hoping and justifying what they wanted to happen. In the weather biz, everyone is wrong sometimes but we have an opportunity to learn from it every day. In fact, people will often tell weatherman jokes related to the meteorologist being wrong.
The joke right now is not only how wrong the climate models are but that there are so many still using them…………..and even worse, all the people that still believe the ones using them.
There is no “social cost of carbon”. It an imaginary “cost” so it follows that any means to calculate SCC will be phony as well.
J. Peden (4:25PM),
The only Mark who posted above you was Mark XR who was clearly NOT taken in by Pindyck. Some of the rest of us were, but, not Mark. Why do you say that Mark XR took “the bait and swallowed it whole?”
Janice
These guys know from whence their grant money comes….
IN the first they present to the realists who see science and the lie of CAGW for what it is. In the next breath they say, even though the tools we us as predictors are crap, we should do it anyway…
Politicians to the end..
Mark XR says:
August 14, 2013 at 3:10 pm
I do hope you aren’t taking the author’s flawed attempt keeping with The Cause as some sort of refutation of his actual conclusions. Seriously, that would be a shame.
From the quote you provided:
In other words, “let’s gamble with our future based on tools we just got done demonstrating are useless.” Yeah, such a good policy. Plan for everything we think could go wrong, then ask forgiveness when we are all impoverished and unable to adapt to everything that does go wrong.
and then the ultimate in ignorance:
When has any government willingly given up power it has forcefully taken from the people it serves? Seriously, when?
.
Mark
Those who boast about modelling will never wake up. They are rocking themselves to sleep in their own egos. Of course money helps to numb their ‘science.’
Mark T,
Re: Mark XR (and others who pointed out Pindyck’s pro-CAGW views)
Good point. I assumed that Mark XR was simply disregarding but not disputing Pindyck’s well-reasoned exposure of the above models as flawed. Perhaps, Mark XR did throw the baby out with the bath water. Only Mr. XR knows!
My main reason for commenting (again!), here, is not to defend XR, but, given that I supported XR above, to make it clear that I AGREE with Pindyck’s analysis of the models (but NOT with his CAGW views).
[Note: vis a vis Peden’s scoffing above, it doesn’t logically follow from XR’s neglecting to say he approved of Pindyck’s analysis that XR was fooled into rejecting that analysis simply because Pindyck is a government boot licker.]
Janice
In other news, water is wet, and the Pope is Catholic….
Who says that any ACTUAL computer code was written and run to generate their charts? They could just as easily have put numbers into Excel, which according to the “accuracy” of their prognostications, they did.
Jail time for all of them in their precious “melting” Arctic, as it’s the only place big enough to accommodate all the liars until they freeze to death, with a complimentary sand-castle bucket and swim togs in hand!
” But mine goes to 11. ” – Sorry but a Spinal Tap reference just seems so appropriate 🙂
Then they must have improved a lot recently 🙂
RERT says:
August 14, 2013 at 3:27 pm: “…If you can’t figure out the value of a mining stock, how in God’s name are you going to figure out the value of something where timescales are longer and essentially everything is unknown in form as well as value?…”
Discounted cash flow modeling works great when one knows – or can estimate a reasonable probability spread for – the key elements of a project. When, for example, one can estimate the capital cost and duration of construction; the cost to strip a given quantity of overburden; the tonnage mined, grade, and metallurgical recovery of metal; etc., etc. And all this is compared to investing a like amount of money in T-bills or some such (or another project). When one starts waving his arms, then anything can come out of one’s DCF model. I doubt “climate projections” or SCC come anywhere near the certainty of a mining or oil project that is being evaluated on the eve of financial commitment.
these are not climate models.
just so you know.
I think the perfect update to this story would be an illustration by example. I’m sure it would be possible to create a model whose output almost exactly duplicates the IPCC predictions. But instead of using the parameters hand picked by the CAGW crowd to produce the desired results, use a set of similarly hand picked but completely nonsensical parameters (i.e. dog/cat ratio in US, average Sumo wrestler weight, CAGW researcher salary, etc.) to illustrate the absurdity of hand picking the parameters in the first place.
Steven, no they’re not climate models, but they necessarily take the dubious projections of the climate models as their inputs, and multiplying the error of those by their own error factor.
My criticism of IAMs should not be taken to imply that because we know so little,
nothing should be done about climate change right now, and instead we should wait until
we learn more. Quite the contrary. One can think of a GHG abatement policy as a form of
insurance: society would be paying for a guarantee that a low-probability catastrophe will
not occur (or is less likely).
This is the Precautionary Principle as espoused by Jerome Ravetz. It is one of those things that sounds reasonable on the surface. The stakes are high, the decisive information uncertain, therefor it is most logical to pursue the “safe” path, just in case. The problem with this sort of reasoning is that it falls flat on its face the moment we attempt to apply it to all situations instead of just one situation. Examples:
1. We could be descending into an ice age. The facts being uncertain and the stakes high, we should be producing as much CO2 as possible to fend it off.
2. The earth could be hit by a planet killer asteroid at any moment. The facts being uncertain and the stakes high, we should be putting every possible resource into the construction of underground bunkers deep enough that humanity can live there until the surface becomes habitable again.
3. There could be a nuclear war at any moment, the facts being uncertain and the stakes high….
4. A virus mutation could wipe out (insert crop of choice here) at any moment….
5. Aliens might invade…
6. Zombies might be real….
7. A giant dormant volcano might blow its stack, resulting in global cooling….
8. A giant dormant volcano might blow its stack, resulting in global warming…
I’m sure people can come up with a very long list of things that are very possibly going to happen, many of which have a higher chance of happening than CAGW. To which do we apply the Precautionary Principle given that they are ALL high stakes, facts uncertain? Not to mention that against each we must weight the results of our actions. Energy poverty kills, and does so with a great deal of certainty. Who would buy a home insurance policy which requires that you burn down 1/4 of your house every 5 years and only pays off if some other cause burns it down entirely?
The Precautionary Principle is a ruse to make the nonsensical appear logical. It is a mind trick, nothing more, and should be read in the context of this study as just that. A mind trick added to the end of an otherwise factual paper.
DonShockley;
But instead of using the parameters hand picked by the CAGW crowd to produce the desired results, use a set of similarly hand picked but completely nonsensical parameters
>>>>>>>>>>>>>>>
I favour the price of stamps, which are clearly correlated to temps:
http://upload.wikimedia.org/wikipedia/commons/b/b0/US_Postage_History.svg