Author: Tom

Energy rich or poor?

The Energy Collective echoes amazement at unconventional oil and gas,

Yergin, vice chairman of IHS CERA:

“The United States is in the midst of the ‘unconventional revolution in oil and gas’ that, it becomes increasingly apparent, goes beyond energy itself.

…

“Owing to the scale and impact of shale gas and tight oil, it is appropriate to describe their development as the most important energy innovation so far of the 21st century. … It is striking to think back to the hearings of even just half a decade ago, during the turmoil of 2008, when it was widely assumed that a permanent era of energy shortage was at hand. How different things look today.”

Mary J. Hutzler, Institute for Energy Research:

“The United States has vast resources of oil, natural gas, and coal. In a few short years, a forty-year paradigm – that we were energy resource poor – has been disproven. Instead of being resource poor, we are incredibly energy rich.”

Abundance is often attributed to a technical miracle, brought about by government R&D into unconventional fossil fuels. The articulated mental model is something like the following:

But is this really a revolutionary transition from scarcity to abundance, was it a surprise, and should technology get all the credit? I don’t think so.

(Abundance/Scarcity) = 1.03?

Contrast the 1995 and 2012 USGS National Assessments of onshore resources:

Resources, on an energy basis (EJ). Cumulative production from EIA; note that gas production data begins in 1980, so gas cumulative production is understated.

In spite of increasing unconventional resources, there’s actually less oil than there was, mainly because a lot of the 1995 resource has since been produced. (Certainly there are also other differences, including method changes.) For gas, where one can make a stronger case for a miracle due to the large increase in unconventional resources, the top line is up a whopping 3%. Even if you go with EIA/INTEK‘s ~2x larger estimate for shale gas, resources are up only 35%.

Call me conservative, but I think an abundance revolution that “disproves” scarcity would be a factor of 10 increase, not these piddly changes.

You could argue that the USGS hasn’t gotten the memo, and therefore has failed to appreciate new, vast unconventional resources. But given that they have reams of papers assessing unconventional fields, I think it more likely that they’re properly accounting for low recoverability, and not being bamboozled by large resources in place.

Reserves involve less guesswork, but more confounding dynamics. But reserves tell about the same story as resources. Oil reserves are more than 40% off their 1970 peak. Even gas reserves have only just regained the levels achieved 40 years ago.

EIA

Surprise?

In 1991, USGS’ Thomas Ahlbrandt wrote:

Unconventional natural gas resources are also becoming increasingly viable. Coalbed methane, which accounts for about 25 percent of potential natural gas resources in the U.S., will displace nearly a trillion cubic feet (TCF) of gas from conventional resources in the near term and perhaps several TCF by the turn of the century. Similarly, production of gas from low permeability resources may displace some production of conventional gas as increasingly smaller conventional accumulations are developed. Coalbed methane and tight gas, both abundant in the Rocky Mountain and Appalachian regions, will likely experience significant production increases. Optimistic scenarios suggest that tight gas and coalbed methane resources may provide more domestic natural gas production than conventional resources by the year 2010. Horizontal drilling technology will most likely unlock the large currently uneconomic gas resources in tight reservoirs. Technologies like this will most certainly change the status of what are presently considered unconventional resources.

I’d call that a “no.”

Should we be surprised to see supply increasing in the current price environment? Again, I’d say no. The idea that oil and gas have supply curves is certainly much older than its appearance in the 1995 USGS assessment. Perhaps the ongoing increase in shale gas development, when prices have collapsed, is a bit surprising. But then you have to consider that (a) drilling costs have tanked alongside the economy, (b) there are lags between price, perception, capital allocation, and production, and (c) it’s expectations of price, not current prices, that drive investment.

Does tech get the credit?

Certainly tech gets some credit. For example, the Bakken oil boom owes much to horizontal drilling:

EIA

But there’s more than tech going on. And much of the tech evolution is surely a function of industry activity funded out of revenue or accumulated through production experience, rather than pure government R&D.

If tech is the exclusive driver of increasing abundance, you’d expect costs and prices to be falling. Gas prices are indeed well off their recent peak, though one could wonder whether that’s a durable circumstance. Even so, gas is no cheaper than it was in the 90s, and more costly than in the pre-OPEC era. Oil isn’t cheap at all – it’s close to its historic highs.

So, if there’s anything here that one might call a tech fingerprint, it would have to be the decline in gas prices post-mid-2008. But that coincides better with the financial crisis than with the gas boom.

Cost data are less current, but if anything the cost picture is less sanguine. “Real gas equipment costs are 12 percent higher and operating costs are 37 percent higher than for the base year of 1976,” says EIA.

Bottom Line

First, let’s not kid ourselves. There’s less oil and gas under US soil than there has ever been.

Technology has at best done a little more than keep the wolf from the door, by lowering the cost of exploration and development by enough to offset the increases that would result from increasing physical scarcity.

It’s possible that the effects on shale and tight gas cost and availability have been dramatic, but there are plausible alternative hypotheses (financial crisis, moving up supply curves, and delays in production capital investment) for current prices.

Personally, I doubt that technology can keep up with physical scarcity and demand growth forever, so I don’t expect that gas prices will continue walking back to 1970 or 1960 levels. The picture for oil is even worse. But I hope that at some point, we’ll come to our senses and tax CO2 at a level high enough to reverse consumption growth. If that happens abruptly enough, it could drive down wellhead prices.

None of this sounds like the kind of tailfins and big-block V8 abundance that people seem to be hoping for.

 

 

Equation Soup

Most climate skepticism I encounter these days has transparently crappy technical content, if it has any at all. It’s become boring to read.

But every once in a while a paper comes along that is sufficiently complex and free of immediately obvious errors that it becomes difficult to evaluate. One recent example that came across my desk is,

Polynomial cointegration tests of anthropogenic impact on global warming Continue reading “Equation Soup”

Greek oil taxes – the real story

A guest post from Ventana colleague Marios Kagarlis, who writes about the NYT article on Greek heating oil taxes:

The problems in Greece are interdependent and all have their roots at the fact that the model of government that has been the status quo in Greece since WWII isn’t working and needs radical change, but the people who run the system know no other way, so the problems keep compounding with no solution in sight.There used to be two tiers of taxation for oil: one was for heating oil, which was relatively low, and the other was for oil used for all other purposes (e.g. for diesel cars etc) which was taxed at about 100% over the fuel cost.

Because of the inability of the government institutions to enforce the laws in Greece (which on paper are tough but in practice are not enforced because the system is incompetent), there has been widespread abuse of this: from refineries to gas stations, many oil merchants have been branding diesel as heating oil to evade the tax, and then selling at as non-heating oil, doubling their profit and ripping off both the consumers and the government.

The government has for years been attempting (supposedly) to crack down on this, with pitiable results. The international lenders have demanded from the Greek government, as a precondition for the continuation of the bailout installments paid every now and then (essentially going in their entirety toward servicing past debt, as opposed to relieving the economy), to crack down on tax evasion via illegal diesel sales of ‘heating oil’ as non-heating diesel. Because the tax collection system is broken and cannot control the diesel market or collect the taxes due, the Greek government had to do something quickly to meet the lenders’ demands. And this was the best they could come up with…

So they finally decided to do away with the two separate tiers of taxation and tax all oil as non-heating oil. To make up for the huge rise in cost to the end consumer they established obscure and bureaucratic criteria for lower income families to submit applications to the government for partial reimbursement of the extra tax, the idea being that this would deprive the sellers from a means to cheat and would still enable end consumers in need to get reasonably priced heating oil after reimbursements. However this didn’t work and instead people just massively stopped using oil for heating, which is by far prevalent in Greece (another government failure, for a country with no oil resources and lots of sun and wind). There are entire older building blocs in cities that were built without fireplaces (which up until recently in modern city apartments were more of a symbol of affluence than of any practical use – people essentially never using them) that have just turned off heating altogether, and fights amongst tenants are commonplace for disagreements over whether to turn on heating or not (which in older buildings is collective so it’s heating for all or for none). Those who cannot afford it just don’t pay so sooner or later most buildings in working class neighborhoods are forced to abandon central heating and sustain the cold or improvise.

Because the government again hadn’t foreseen any of this, and wood burning was never particularly widespread in Greece, there had not been standards for wood or pellet burning stoves. So the market is flooded with low quality wood-burning stoves which are totally inefficient and polluting. So suddenly from December the larger cities in Greece are filled with smog and particulates for the first time from inefficient wood-burning stoves, and from burning inappropriate wood (e.g. people burn disused lacquered furniture at their fireplaces, which is very polluting). Cases of asthma and respiratory illnesses in the larger cities since December have skyrocketed. In the meantime forests and even city parks are raided daily by desperate unemployed people who cannot afford heating (especially in northern Greece), who cut down any trees they can get their hands on.

It’s hard to see that there can be any short term solution to this, in the middle of the worst economic crisis Greece has faced since WWII.

Marios lives in Athens.

Oil tax forces single cause attribution folly

A silly NYT headline claims that Rise in Oil Tax Forces Greeks to Face Cold as Ancients Did.

The tax raised the cost of heating oil 46%, which hardly sends Greece back to the Bronze Age. Surely the runup in crude prices by a factor of 5 and a depression with 26% unemployment have a bit to do with the affordability of heat as well?  And doesn’t the unavailability of capital now make it difficult for people to respond sensibly with conservation, whereas a proactive historic energy policy would have left them much less vulnerable?

The kernel of wisdom here is that abrupt implementation of policies, or intrusion of realities, can be disruptive. The conclusion one ought to draw is that policies need to anticipate economic, thermodynamic, or environmental constraints that one must eventually face. But the headline instead plays into the hands of those who claim that energy taxes will doom the economy. In the long run, taxes are part of the solution, not the problem, and it’s the inability to organize ourselves to price externalities that will really hurt us.

Update: the real story.

Real estate appraisal – learning the wrong lesson from failure

I just had my house appraised for a refinance. The appraisal came in at least 20% below my worst-case expectation of market value. The basis of the judgment was comps, about which the best one could say is that they’re in the same county.

I could be wrong. But I think it more likely that the appraisal was rubbish. Why did this happen? I think it’s because real estate appraisal uses unscientific methods that would not pass muster in any decent journal, enabling selection bias and fudge factors to dominate any given appraisal.

When the real estate bubble was on the way up, the fudge factors all provided biased confirmation of unrealistically high prices. In the bust, appraisers got burned. They didn’t learn that their methods were flawed; rather they concluded that the fudge factors should point down, rather than up.

Here’s how appraisals work:

A lender commissions an appraisal. Often the appraiser knows the loan amount or prospective sale price (experimenters used to double-blind trials should be cringing in horror).

The appraiser eyeballs the subject property, and then looks for comparable sales of similar properties within a certain neighborhood in space and time (the “market window”). There are typically 4 to 6 of these, because that’s all that will fit on the standard appraisal form.

The appraiser then adjusts each comp for structure and lot size differences, condition, and other amenities. The scale of adjustments is based on nothing more than gut feeling. There are generally no adjustments for location or timing of sales, because that’s supposed to be handled by the neighborhood and market window criteria.

There’s enormous opportunity for bias, both in the selection of the comp sample and in the adjustments. By cherry-picking the comps and fiddling with adjustments, you can get almost any answer you want. There’s also substantial variance in the answer, but a single point estimate is all that’s ever reported.

Here’s how they should work:

The lender commissions an appraisal. The appraiser never knows the price or loan amount (though in practice this may be difficult to enforce).

The appraiser fires up a database that selects lots of comps from a wide neighborhood in time and space. Software automatically corrects for timing and location by computing spatial and temporal gradients. It also automatically computes adjustments for lot size, sq ft, bathrooms, etc. by hedonic regression against attributes coded in the database. It connects to utility and city information to determine operating costs – energy and taxes – to adjust for those.

The appraiser reviews the comps, but only to weed out obvious coding errors or properties that are obviously non-comparable for reasons that can’t be adjusted automatically, and visits the property to be sure it’s still there.

The answer that pops out has confidence bounds and other measures of statistical quality attached. As a reality check, the process is repeated for the rental market, to establish whether rent/price ratios indicate an asset bubble.

If those tests look OK, and the answer passes the sniff test, the appraiser reports a plausible range of values. Only if the process fails to converge does some additional judgment come into play.

There are several patents on such a process, but no widespread implementation. Most of the time, it would probably be cheaper to do things this way, because less appraiser time would be needed for ultimately futile judgment calls. Perhaps it would exceed the skillset of the existing population of appraisers though.

It’s bizarre that lenders don’t expect something better from the appraisal industry. They lose money from current practices on both ends of market cycles. In booms, they (later) suffer excess defaults. In busts, they unnecessarily forgo viable business.

To be fair, fully automatic mass appraisal like Zillow and Trulia doesn’t do very well in my area. I think that’s mostly lack of data access, because they seem to cover only a small subset of the market. Perhaps some human intervention is still needed, but that human intervention would be a lot more effective if it were informed by even the slightest whiff of statistical reasoning and leveraged with some data and computing power.

Update: on appeal, the appraiser raised our valuation 27.5%. Case closed.

Positive feedback drives email list meltdown

I’m on an obscure email list for a statistical downscaling model. I think I’ve gotten about 10 messages in the last two years. But today, that changed.

List traffic (data in red).

Around 7 am, there were a couple of innocuous, topical messages. That prompted someone who’d evidently long forgotten about the list to send an “unsubscribe me” message to the whole list. (Why people can’t figure out that such missives are both ineffective and poor list etiquette is beyond me.) That unleashed a latent vicious cycle: monkey-see, monkey-do produced a few more “unsub” messages. Soon the traffic level became obnoxious, spawning more and more ineffectual unsubs. Then, the brakes kicked in, as more sensible users appealed to people to quit replying to the whole list. Those messages were largely lost in the sea of useless unsubs, and contributed to the overall impression that things were out of control.

People got testy:

I will reply to all to make my point.

Has it occurred to any of you idiots to just reply to Xxxx Xxxx rather than hitting reply to all. Come on already, this is not rocket science here. One person made the mistake and then you all continue to repeat it.

By about 11, the fire was slowing, evidently having run out of fuel (list ignoramuses), and someone probably shut it down by noon – but not before at least a hundred unsubs had flown by.

Just for kicks, I counted the messages and put together a rough-cut Vensim model of this little boom-bust cycle:

unsub.mdl unsub.vpm

This is essentially the same structure as the Bass Diffusion model, with a few refinements. I think I didn’t quite capture the unsubscriber behavior. Here, I assume that would-be unsubscribers, who think they’ve left the list but haven’t, at least quit sending messages. In reality, they didn’t – in blissful ignorance of what was going on, several sent multiple requests to be unsubscribed. I didn’t explicitly represent the braking effect (if any) of corrective comments. Also, the time constants for corrections and unsubscriptions could probably be separated. But it has the basics – a positive feedback loop driving growth in messages, and a negative feedback loop putting an end to the growth. Anyway, have fun with it.

Computing and networks have solved a lot of problems, like making logistics pipelines visible, but they’ve created as many new ones. The need for models to improve intuition and manage new problems is as great as ever.

Climate incentives

Richard Lindzen and many others have long maintained that climate science promotes alarm in order to secure funding. For example:

Regarding Professor Nordhaus’s fifth point that there is no evidence that money is at issue, we simply note that funding for climate science has expanded by a factor of 15 since the early 1990s, and that most of this funding would disappear with the absence of alarm. Climate alarmism has expanded into a hundred-billion-dollar industry far broader than just research. Economists are usually sensitive to the incentive structure, so it is curious that the overwhelming incentives to promote climate alarm are not a consideration to Professor Nordhaus. There are no remotely comparable incentives to the contrary position provided by the industries that he claims would be harmed by the policies he advocates.

I’ve always found this idea completely absurd, but to prep for an upcoming talk I decided to collect some rough numbers. A picture says it all:

Data

Notice that it’s completely impractical to make the scale large enough to see any detail in climate science funding or NGOs. I didn’t even bother to include the climate-specific NGOs, like 350.org and USCAN, because they are too tiny to show up (under $10m/yr). Yet, if anything, my tally of the climate-related activity is inflated. For example, a big slice of US Global Change Research is remote sensing (56% of the budget is NASA), which is not strictly climate-related. The cleantech sector is highly fragmented and diverse, and driven by many incentives other than climate. Over 2/3 of the NGO revenue stream consists of Ducks Unlimited and the Nature Conservancy, which are not primarily climate advocates.

Nordhaus, hardly a tree hugger himself, sensibly responds,

As a fifth point, they defend their argument that standard climate science is corrupted by the need to exaggerate warming to obtain research funds. They elaborate this argument by stating, “There are no remotely comparable incentives to the contrary position provided by the industries that he claims would be harmed by the policies he advocates.”

This is a ludicrous comparison. To get some facts on the ground, I will compare two specific cases: that of my university and that of Dr. Cohen’s former employer, ExxonMobil. Federal climate-related research grants to Yale University, for which I work, averaged $1.4 million per year over the last decade. This represents 0.5 percent of last year’s total revenues.

By contrast, the sales of ExxonMobil, for which Dr. Cohen worked as manager of strategic planning and programs, were $467 billion last year. ExxonMobil produces and sells primarily fossil fuels, which lead to large quantities of CO2 emissions. A substantial charge for emitting CO2 would raise the prices and reduce the sales of its oil, gas, and coal products. ExxonMobil has, according to several reports, pursued its economic self-interest by working to undermine mainstream climate science. A report of the Union of Concerned Scientists stated that ExxonMobil “has funneled about $16 million between 1998 and 2005 to a network of ideological and advocacy organizations that manufacture uncertainty” on global warming. So ExxonMobil has spent more covertly undermining climate-change science than all of Yale University’s federal climate-related grants in this area.

Money isn’t the whole story. Science is self-correcting, at least if you believe in empiricism and some kind of shared underlying physical reality. If funding pressures could somehow overcome the gigantic asymmetry of resources to favor alarmism, the opportunity for a researcher to have a Galileo moment would grow as the mainstream accumulated unsolved puzzles. Sooner or later, better theories would become irresistible. But that has not been the history of climate science; alternative hypotheses have been more risible than irresistible.

Given the scale of the numbers, each of the big 3 oil companies could run a climate science program as big as the US government’s, for 1% of revenues. Surely the NPV of their potential costs, if faced with a real climate policy, would justify that. But they don’t. Why? Perhaps they know that they wouldn’t get a different answer, or that it’s far cheaper to hire shills to make stuff up than to do real science?