Fossil Fuels

We all know that OPEC colludes to keep oil off the market and prices high. Or do we? There is actually remarkably little agreement on whether OPEC is any good at what it aspires to do. Does membership in OPEC really make countries more likely to constrain their oil output? It’s a question with wide-ranging consequences for everything from the economy to security to climate change. Jeff Colgan has a forthcoming paper (late draft here) in International Organization (IO), the top journal in the academic international relations world, that answers the big “does OPEC matter” question with a resounding No. The paper is an impressive piece of work that mixes multiple tests of OPEC influence with a careful look into why, if OPEC doesn’t influence oil production, so many people continue to believe otherwise. It should make anyone who is utterly convinced that OPEC is the world oil market’s puppetmaster think twice. But I think Colgan goes much too far in confidently claiming that OPEC “has little or no impact” on members’ production. This is particularly true if one asks whether policymakers and market participants, rather than only political scientists, should conclude from his paper that OPEC doesn’t matter. As a corollary, I think he ultimately goes too far in trying to explain why so many people believe in a “myth” – what they believe, at least in its subtler forms, may not actually be a myth at all. Colgan applies four tests to his data; I find the first three largely underwhelming and the fourth far more interesting. The first question he asks is whether entry into OPEC reduces a country’s oil production (relative to trend) and whether exit from OPEC increases it; he finds that OPEC has no detectible influence. But it’s unclear that the counterfactual here is correct. It’s just as plausible that states that enter OPEC are ones that would otherwise see accelerating production (and vice-versa for exits) – after all, being an up-and-coming oil producer is presumably what makes you think about joining OPEC, and being on the decline makes you consider leaving. Colgan’s methodology is borrowed from studies of WTO entry and trade, but it’s not clear that the situations are analogous, since already-accelerating trade presumably isn’t a typical motivation for WTO entry. The second and third tests look at OPEC quotas. One shows that OPEC countries consistently cheat; Colgan acknowledges that this is a weak test given that quotas can be set at levels that anticipate cheating. The other is more persuasive: it shows that OPEC quotas have very little predictive power when it comes to explaining month-to-month variations in OPEC countries’ production. I should pause here for a moment to be clear about what Colgan isn’t claiming. He isn’t claiming that individual OPEC  members (notably Saudi Arabia) don’t exercise market power in ways that prop up the price of oil. What he’s claiming is that to the extent that happens, it’s about individual country decisions, and OPEC membership has nothing to do with it. That’s the right test when you’re asking whether OPEC is an effective cartel. So back to the tests – because the fourth one is the most interesting. Colgan notes, correctly, that OPEC members may restrain production not through short-term quotas but through long-term restraint on oil production investment. This is a popular view. (Some also believe that the OPEC core restrains production through a form of price coordination, a possibility that Colgan briefly raises and then rejects, I think too readily.) And indeed Colgan shows that OPEC membership is a decent predictor of low oil depletion rates. But he then claims to show that this is an artifact: if one allows depletion rates to be influenced by fiscal strength (measured essentially by oil reserves per capita), investment risk, and several other factors along with OPEC membership, one finds that fiscal strength and investment risk help explain depletion rates, and that OPEC membership no longer matters. This is interesting stuff and should make people think hard about whether OPEC has real influence on its members’ behavior. But I’m extremely wary of the strong conclusion for a couple big reasons. First, it’s far from clear that OPEC membership itself doesn’t influence countries’ investment climate. To be certain, leaders don’t wake up and say “I’m an OPEC member – I should have an awful investment climate!”. Attitudes toward investment are, instead, shaped by a much broader range of factors. But having decided to underinvest in oil production, a state is less likely to feel pressure to improve its investment climate, since it has less need to. To be clear, I have no idea whether OPEC membership influences decisions regarding oil production, and hence investment climates, in this way. But Colgan’s methods wouldn’t detect that even if it did. My other big worry has to do with how the paper – following standard political science practice – handles statistical significance. Political scientists search for “truths”. When Colgan says that OPEC has “little or no impact” on members’ production levels, what he means is that he can’t be at least 90 percent certain that OPEC membership influences member countries’ production levels. (More precisely, as best I can tell, he can’t reject with 90 percent or greater confidence the hypothesis that OPEC membership doesn’t influence members’ production levels, so he accepts it.) This may be the right threshold for political science but it’s a dangerous one for policymaking. For example, it turns out that one of Colgan’s tests (#3 in Table 2) allows one to conclude with 75 percent confidence that OPEC membership influences member countries’ production levels (again with the same caveats about double negatives as above). Another test (#4 in Table 2) shows that even if one separates out Saudi Arabia, one can still conclude with 75 percent confidence that OPEC membership influences remaining member countries’ production. And a third test (#5 in Table 2) shows that if one further separates non-Saudi OPEC members into a “core” and a “periphery” one can still conclude with 70 percent confidence that they’re all influenced by OPEC. (One note of caution here: Seventy percent confidence isn’t nothing, but it isn’t as much at one might intuitively think; fifty percent confidence would mean that we have no clue what OPEC influence is. The way one interprets these sorts of numbers should depend strongly on one’s priors, i.e. other pre-existing beliefs about OPEC.) Should a policymaker or market participant write off OPEC because data analysis suggests that there’s only a 75 percent chance (rather than a 90 percent one) that it’s influential? (Or, put a clumsier but slightly more accurate way, should they ignore OPEC because a statistical test can’t conclude with 90 percent confidence that people who say “OPEC doesn’t matter” are wrong?) Of course not. He or she should discount the influence of OPEC in his or her assessment of the costs and benefits of any potential action, given uncertainty about whether OPEC is genuinely influential, but it would be awfully risky to proceed on the assumption that OPEC has no influence at all. In fairness to Colgan, he addresses this indirectly, writing that “it is impossible to affirm the null hypothesis (i.e. to prove that OPEC has no impact)”, and then estimating the impact that OPEC may have had on oil production. He uses several factors (not including OPEC membership) to predict OPEC oil production and then estimates that non-Saudi members under-produced by 6.6 percent relative to that (equivalent to 1.6 million barrels per day in 2009). Colgan asserts that it is “difficult to believe that such an amount is having a major impact on world oil prices”. But there remain three issues here: 1.6 million barrels a day is not a trivial amount of oil; Colgan does his projections based on a data set extending back to 1980 even though analysts typically believe that OPEC restraint based on under-investment is a far more recent phenomenon (Colgan subdivides his data set into shorter time periods elsewhere in the paper but not here); and the estimate of a 6.6 percent percent shortfall presumably has large uncertainties that might mean that OPEC impact is considerably greater. Bottom line? Colgan’s paper should deflate some of the hyper-confident claims that OPEC rigs the world oil market. I hope it sparks some constructive debate. It would be awfully unwise, though, for policymakers or market participants to quickly flip to an equally over-confident belief that OPEC doesn’t matter.

The Department of Energy (DOE) announced this afternoon that it had conditionally approved the application of Freeport LNG Expansion LP and FLNG Liquefaction LLC to export up to 1.4 billion cubic feet of liquefied natural gas (LNG) to countries with which the United States does not have special free trade agreements. I’ve written at some length before about the potential consequences of LNG exports in general. But what might the exports from this particular facility mean? First things first: This is just a DOE approval. Freeport will still need to get a permit from FERC. And, more important, it will still need a solid market for its LNG. There are a lot of credible people out there who believe that U.S. LNG exports will be very small – so small, perhaps, that Freeport will never ship any fuel despite having a permit and a set of contracts (PDF) lined up. What would be the impact, though, if Freeport ultimately did sell LNG at its full approved capacity? Analyses have typically suggested that prices might rise by $0.10-$0.20/MMBtu for every billion cubic feet a day in export demand. That points to a rise of $0.15-$0.30/MMBtu (against a likely base price of $4-6) if the facility ultimately sells LNG at full capacity. Analyses also have typically suggested that somewhere between 50 and 80 percent of exported LNG would come from new production, rather than displaced domestic demand. That translates to 0.7-1.1 bcf/d in additional production. That’s equivalent to between 1-2 percent additional U.S. natural gas supply. With shale gas currently contributing about 30 percent of U.S. gas production, it’s about a 4-6 percent increase in U.S. shale gas output. This increase will be the main source of environmental hazard – the climate impact of Freeport-sized exports will be very small. What about broader economic impacts? Scaling from a study I published a year ago, my instinct is that this is good for the U.S. economy, but ultimately adds less than a billion dollars a year to GDP, and supports perhaps on the order of 10,000 jobs (many of which would employ people who would have been employed elsewhere otherwise). Most of this job growth would be in gas production and related industries. An export plant of this scale will also likely employ a couple thousand people at the peak of construction. How about destinations? Freeport has contracted with BP for half of its capacity and with Osaka Gas and Chubu Electric (both Japanese) for the other half. At least half the output, then, would likely be headed to Asia. It’s also quite possible that much of BP’s capacity would be used to ship LNG to Asia too. This would help Asian buyers gain a bit more leverage with their traditional suppliers, and diversify their risks, but as I argued in congressional testimony a few weeks ago, it’s highly unlikely to be revolutionary. That’s particularly true if you’re looking at just one plant. All told, this approval is good news, with benefits to U.S. relations with other countries even if Freeport never sells a drop of LNG, and the potential for some broader gains if it does. It also reinforces the importance of getting environmental protections right as shale gas production expands.

Climate discussions of late have focused a lot of so-called short-lived forcers. These are substances such as methane and black carbon that don’t stay in the atmosphere for all that long but trap a lot of heat while they’re there. Analysts use global warming potentials (GWPs) as shorthand to compare these gases with carbon dioxide. For example, over a 20-year period, methane traps 72 times as much heat as carbon dioxide, giving methane a 20-year GWP of 72. The problem, as many readers of this blog know, is that it’s never clear what time period one should focus on. Methane may have a 20-year GWP of 72, but it also has a 100-year GWP of 25. Which one should analysts use when thinking about the dangers posed by short-lived forcers? An EPA working paper that I wish I’d read when it was published in January 2011 (it was also published as a peer-reviewed paper in Energy Policy in 2012) suggests a useful way of thinking about this. Instead of focusing on how much heat is trapped, we should be looking at how much damage is done. There’s a huge literature aimed at estimating the damage done by a ton of carbon dioxide, a quantity known as the social cost of carbon (SCC). The literature is highly controversial, in part because damage estimates are uncertain, but also because the results depend sensitively on how deeply you discount the future economic impact of emissions. When the U.S. government estimated the SCC in 2010, for example, it found a value of $21 per ton. But had it assumed a discount rate of 5 percent rather than 3 percent, the answer would have come out at $5, and had it assumed a discount rate of 2.5 percent, the SCC would have been $35. Moreover, had it focused on the 95th percentile of potential damages, it would have found an SCC of $65. Here’s the neat thing that makes looking at damages a great way to think about short-lived forcers: the estimated damages caused by short-lived forcers are a lot less sensitive to the discount rate. That’s because they’re concentrated in the near future, which makes them less sensitive to the choice of discount rate. That makes it easier to approach agreement on what the social costs of short-lived forcers are. So what’s the upshot? According to the EPA authors’ paper, if you assume a 5 percent discount rate, methane is 39 times as damaging as carbon dioxide when integrated over time; if you assume a 3 percent discount rate, methane is only 25 times as damaging, similar to the ratio suggested by the 100-year GWP; and if you assume a 2.5 percent discount rate, that factor drops to 21. (The ratio would be even smaller for the ultra-low discount rates that some have encouraged.) A similar pattern would prevail if one modeled other short-lived forcers. Moreover, if you focus on the 95th percentile damages, you find methane is 27 times worse that carbon dioxide. Those who claim that climate impacts from carbon dioxide emissions are well above the $21 figure used by the U.S. government typically argue for low discount rates and high-end damages to justify their stance. In order to be self-consistent, then, they should be treating methane and other short-lived-forcers based on something closer to their 100-year (or longer) GWPs than the 20-year ones that have become popular in some quarters in recent years.

Cheap natural gas has split the climate debate into two camps. One celebrates the development, emphasizing that natural gas cuts emissions when it replaces coal, and arguing that abundant gas reduces emissions as a result. The other bemoans the news, noting that inexpensive natural gas makes it tougher for zero-carbon energy to compete and arguing that this will ultimately result in higher, not lower, emissions. Which view is right? Exploring a set of simulations just released as part of the Annual Energy Outlook published by the Energy Information Administration (EIA) provides some neat insight. For the first time, the EIA simulates not only the impact of low natural gas prices and the impact of carbon pricing but also what happens when you combine the two. The results are really interesting. The plot below shows the two natural gas price assumptions that the EIA looks at. (I made all the plots using the EIA’s awesome AEO Table Browser.) The high natural gas price scenario is based on what analysts currently believe the natural gas resource looks like. The low price scenario results from assuming that each gas (and oil) well yields twice as much fuel as currently believed; well spacing declines so that more wells can be packed into a given area; and undiscovered oil and gas resources are 50 percent higher than currently assumed, among other tweaks. Expected prices, you’ll notice, diverge pretty sharply over time. If you assume no price on carbon, you end up with the emissions in the figure below. Super-cheap natural gas cuts emissions (though barely) for the next couple decades. After that it actually begins to make things (barely) worse. The next figure shows what happens when you put a modest price on carbon. Here the assumed carbon price is ten dollars a ton starting in 2013 and rising 5 percent annually through 2040. Now what you find is that cheap gas consistently helps. The carbon price cuts emissions relative to business as usual – but the carbon price combined with cheap gas does even more. Things get even more interesting, though, when you step the carbon price up a bit. The next figure assumes that a carbon price starts at fifteen dollars in 2013. (The other details remain the same.) Now we’re back to a pattern that’s a bit more like the reference case: Cheap gas helps for the next couple decades before becoming a climate liability later. Perhaps the most interesting chart, though, is the final one, displayed below. It shows what happens when you’ve got a carbon price that starts at twenty-five dollars in 2013. Now low natural gas prices help, though almost imperceptibly, for the next decade. After that, though, they actually hurt, and by the time you get out to 2030 and 2040, the penalty imposed by cheap gas becomes pretty large. There are, as usual, caveats galore here. This is one model, and one set of technology and market assumptions, so its results should be treated with great care. It says nothing about the costs of emissions reductions -- and abundant natural gas can make hitting the same emissions trajectory cost less. Moreover different people will interpret these figures in differing ways. Some will say the results they show that natural gas is bad news (at least in the long run) for climate change. Other will argue that they offer a series of misleading comparisons: in a world with cheap natural gas, it may be more politically feasible to impose a higher carbon price, and if that’s true, cheap gas could still mean considerably lower long-run emissions. A third camp (undoubtedly dominated by economists) might argue that these projections simply show that cheap natural gas might make a rational carbon policy consistent with higher emissions than it otherwise would be. Who’s right? That’s a tough question. There’s a lot more to be analyzed here, and even more that’s probably not amenable to neat and clean analysis. What’s for certain, though, is that the consequences of natural gas for U.S. emissions are more complex and intriguing than most people have assumed.

I wrote last week about a looming problem with the Renewable Fuels Standard (RFS2) that has parts of industry and many policy analysts concerned about rising gas prices. In this post I want to write about one regulatory tweak that might help deal with the problem without gutting the mandate: adding something like a safety valve to the RFS2. The Problem Let’s quickly recap what’s going on. The EPA has mandated that an increasing amount of ethanol be blended into fuel. Because U.S. fuel use is declining, if it were blended uniformly, the fraction of ethanol in fuel would likely exceed 10 percent, the so-called “blend wall” beyond which many U.S. vehicles can’t use (or at least are wary of using) the fuel. The resulting dynamics could, in principle, drive up prices for Renewable Identification Numbers (RINs), an instrument that refiners and blenders need to submit in order to demonstrate RFS2 compliance. That could push fuel prices way up. As several people have noted, the way around this is to grow sales of E85, a blend of 85 percent ethanol and 15 percent gasoline that a subset of U.S. vehicles (flex-fuel cars and trucks) can use. If, say, the EPA effectively mandates that the U.S. fuel supply should be 11 percent ethanol, one way to meet that would be to have (roughly) 99 percent of fuel sales be E10 (10 percent ethanol) and the other 1 percent be E85. This would avoid the blend wall and let the mandate do its job. The biggest problem that analysts have with this is that E85 has never been a significant seller. That’s largely because it’s always been more expensive than E10 or plain gasoline on an energy-equivalent basis. Very few are going to buy E85 if it costs more. Barriers to E85 In a fascinating draft paper (“The Blend Bump”, forthcoming later this month), Phil Verleger points out something important: as RIN prices rise, it should become profitable to sell E85 at an ever greater discount. When you sell E85, you generate a large volume of RINs, most of which you don’t need to comply with your mandate obligations. You can sell that RIN surplus to refiners and blenders who sell E10 or pure gasoline and who need more RINs in order to meet their obligations. How high would RIN prices need to rise to pump up E85 sales? A precise estimate is difficult. As Verleger notes, however, it’s pretty easy to establish an upper bound by asking a simple question: how valuable would RINs need to be to persuade companies to give away E85 for free? He estimates that, given current ethanol prices, RINs would need to sell for $3.50 to make that happen on the spot market, and for $5.00 to get sellers to give away the stuff at retail too. If RIN prices rose to $3.50, it would increase the prices of fuel by about 35 cents. Since this is an upper bound, one should in principle expect prices to rise by less than that – Verleger estimates that, given current RBOB gasoline and ethanol prices, if all it took to push E85 into the market was a 10 percent discount to E10 on an energy-adjusted basis, RINs would only need to sell for about $1.18 for the system to work. What I find particularly interesting about Verleger’s paper, though, is the next step: it asks whether there might be reasons that this dynamic could fail to unfold. He flags three factors but highlights one particularly critical one. When a company sells E85, they generate surplus RINs immediately. They are unlikely, however, to find an immediate buyer, since most refiners and blenders wait until closer to the end of each compliance year to buy the RINs that they need. In the interim, the E85 sellers face a serious regulatory risk: given growing calls from parts of industry and Congress to investigate the RFS2, they have legitimate reason to worry that the mandate will be waived or watered down. In that case, their RINs will lose value, and their E85 gambit might fail to pay off. Given that prospect, they might not sell E85 (and generate lots of RINs) in the first place. In that case we’d stuck with the sort of debacle that many have warned of. A Safety Valve? That leads to my own suggestion for a possible policy tweak. We need a way to increase the credibility of the mandate without risking an unacceptable price spike. If E85 sellers can be made confident that the RFS2 will be sustained, there’s a decent chance that they’ll sell a substantial volume of their product, and that the RFS2 will be met. (No one can know for sure, though, particularly because there many not be enough E85 pumps to ramp up sales quickly enough.) If they are afraid that the mandate won’t hold, though, they won’t sell much E85; their predictions will become self-fulfilling, as fuel prices rise strongly and politicians react by severely weakening the mandate. Congress could largely eliminate this latter possibility by adding a safety valve to the RFS2: it could commit the U.S. government now to selling an unlimited quantity of RINs in the future at some preset price. That price would need to be set high enough to keep E85 sales profitable.  If, for example, the safety valve were set somewhere between $1 and $2, strong incentives to sell E85 at a discount would probably remain, since sellers might be able generate decent volumes RINs for less than the safety valve price that way. (Picking a precise level for a safety valve would require considerably more robustness analysis than this blog post permits.) And if people are right that E85 provides a smooth way around the blend wall, no one will ever need to buy RINs from the government in the end. At the same time, the price would need to be set low enough to reassure everyone that the RFS2 won’t raise fuel prices too much, even if E85 fails to penetrate the market strongly. That would remove the risk that scared policymakers would drastically weaken the mandate or waive it entirely, again helping E85 sellers gain confidence. The same $1-$2 price could do that: it would allow fuel prices to rise by no more than 10-20 cents. Some will find this idea odd: wouldn’t a floor price for RINs, rather than a ceiling, be the best way to incentivize more production of E85? The essential thing to keep in mind here is that the goal of the tweak would be to reinforce the political credibility of the RFS2, and then to let the market work. A ceiling, not a floor, is what’s needed to do that. To be certain, it’s far from clear that the RFS2, even with this tweak, would pass a cost-benefit test. The current situation should also provide lessons on how not to design mandates (more on that in another post). But with the mandate in place, there could be serious damage from deeply weakening it, since that would harm the credibility (and hence effectiveness) of any future mandates. That should be reason enough to look for careful ways of modifying the mandate that protect consumers while maximizing the odds that it will survive largely intact.

Prominent economic commentators have argued the cases for significantly weaker currencies in each of the world’s major economies – in particular, the United States, the eurozone, Japan, and the UK. As these four economies represent over half of the global economy, it’s clear that they can’t all accomplish this feat. It’s also far from clear that they should all want to. Take the UK, where the FT's Martin Wolf has led the charge for “further depreciation of the real exchange rate.” John Maynard Keynes, belying his reputation as a devaluationist, had argued passionately against a weaker pound in 1945 on the basis of terms of trade: that is, the UK would, broadly, have to give up more domestic goods in return for the same quantity of foreign goods. “In [our] circumstances, you can’t imagine anything more foolish,” he said, “than to be trying to sell [our] exports at quite unnecessarily low prices.” Today he might highlight inflation. As shown in today’s Geo-Graphic, currency depreciation is likely to have a much more adverse effect on inflation in the UK than in the United States, the eurozone, or Japan, owing to much higher imports relative to GDP. UK consumer price inflation is already running at a relatively high 2.8%, and the Bank of England’s own analysis suggests that a 20% sterling depreciation risks pushing the price level up 6 percentage points higher than it would otherwise be. Steil: The Battle of Bretton Woods Bank of England: Inflation Report February 2011 Wolf: Weaker Pound Is Welcome but No Panacea Financial Times: Weakening Pound Raises Stagflation Fears

An esoteric fight of the Renewable Fuels Standard (RFS2), which mandates that the United States use an increasing volume of ethanol each year, has become a bit more prominent in recent weeks, with some accusing the mandate of contributing to rising gasoline prices in new and troubling ways. I remain perplexed as to what exactly is going on – more on that a bit further down – but I do find the defense from the Renewable Fuels Association, published last week in the form of a white paper commissioned from Informa Economics, hugely unpersuasive. The basics of what’s happening are broadly agreed. There is controversy over whether large numbers of U.S. cars can safely use fuel that contains more than 10 percent ethanol. For all practical purposes, then, refiners and blenders don’t want to use more than 10 percent ethanol in the fuel they produce. Meanwhile, the RFS2 is mandating increasing use of ethanol – and, because of high gasoline prices and improving fuel economy, total U.S. fuel consumption is falling at the same time. This squeeze from both sides means that the United States has hit the “blend wall” – the point at which it can’t use any more ethanol without breaching the 10 percent threshold – far earlier than anyone expected. It is impossible to comply with the volume requirements of RFS2 and avoid the blend wall at the same time. For the time being, though, there’s a way out. In years when ethanol producers make more ethanol than the mandate requires, they generate a surplus of something called Renewable Identification Numbers, or RINs. They can bank those for the next year. Before 2012, when ethanol subsidies stopped, producers built up a surplus of RINs; part of that surplus remains. Blenders and refiners can buy these RINs instead of actually blending ethanol into their fuel. That’s how they’re dealing with the current crunch: they’re buying RINs instead of blending the full mandated volume of ethanol. The problem is that there’s a limited supply of RINs, so prices for them have skyrocketed. It’s those super-high RIN prices that people are now blaming for higher prices at the pump. The big question is this: How much are high RIN prices actually inflating fuel prices? And how might that impact evolve? The new industry association paper claims that the impact is tiny, and that, once you factor in the relatively low price of ethanol, RFS2 is still producing net benefits for consumers. But their analysis doesn’t hold up. Let’s start with the biggest whopper. The white paper observes that wholesale gasoline (they measure this in Chicago) was $2.81/gallon on average this year, while wholesale ethanol cost $2.37/gallon. They thus claim that blending ethanol into gasoline lowers prices. Set aside for a moment some subtle issues about how prices are set; what’s amazing here is that they apparently don’t account for the fact that a gallon of gasoline has 50 percent more energy than a gallon of ethanol. Blending ethanol lowers the price of a gallon of fuel – but that gallon of fuel now gets you less mileage in your car. The net result is to increase the cost of driving. Claiming in this way that ethanol blending lowers fuel costs is like claiming that buying smaller boxes of cereal lowers the cost of getting yourself a nutritious breakfast. Now for the more complicated part: the RINs. The industry white paper estimates the number of RINs that will need to be purchased in order to meet the RFS2 mandate and spreads their cost across the full U.S. fuel supply; they use that to estimate a price increase of between $0.004 and $0.02 due to RIN purchases. But prices aren’t set by average costs. What sets the price of fuel at the pump is the marginal cost, i.e. the cost of the most expensive gallon of fuel that’s sold. The big question, then, is what that marginal gallon is. The answer is either (a) a gallon of gasoline plus an appropriate volume of RINs, or (b) a gallon of fuel that’s a mix of gasoline and ethanol. (Perhaps it could be something in between too.) I can’t quite wrap my head around the answer –that might be the subject for another post or a real study (or someone will email along a good analysis) – but it certainly isn’t what the industry white paper claims. My instinct is that if the answer isn’t (a), things will eventually end up there, since the cost of ethanol is bounded above, while the price of RINs isn’t. And, if that’s right, we may see a big pump price run-up before too long. It’s critical that we think through this now. At some point in the not-too-distant future, unless U.S. fuel demand rebounds, the surplus of RINs will presumably be exhausted. At that point all bets are off when it comes to the market impacts. Best to figure this out now, and come up with good policy adjustments if those are needed, rather than deal with this when things are much worse.

Want to understand the energy challenges the world might face in the future? There are few better places to turn than this year’s BP Energy Outlook to 2030, an annual publication that shows the company’s projections for energy supply and demand over the next two decades. The three graphs below highlight some of the trends likely to define the energy landscape in the years ahead, in BP’s view. Two decades from now, a world with more people and higher average incomes will mean more demand for energy. That shouldn’t be a surprise. What’s more striking is to see where all this growth will happen. In BP’s forecast, low and medium income economies outside the OECD will account for a full 90 percent of population growth between now and 2030, and their GDP will climb much higher. These same countries will also contribute to 90 percent of all the energy demand growth over that time, roaring ahead of the developed world. In the developed world, energy consumption will barely tick up. Just 0.3 percent per year, in fact, until 2030. That would actually be a decline in per capita terms. Again, almost all of the growth in energy consumption is in non-OECD countries. And where will the world get its energy? If BP is right, fossil fuels will still dominate the energy mix. Renewables will be the fastest growing sources of energy, but given the relatively tiny piece of the pie they make up today, they’ll still be far from dominant. No other energy sources will see the scale of consumption growth that coal and natural gas will, in absolute terms. Demand for electricity will grow by leaps and bounds. China and India alone will account for a huge part of that new power consumption. The OECD will only see a little growth in that area, relatively speaking, for all its economic clout. The developed world will actually use less energy for transportation than it does now. Again, low and middle income countries will be at the very center of the picture when it comes to growing appetite for energy over the next two decades. There will undoubtedly be surprises between now and 2030. If the last decade has taught us anything about energy, it’s that old truths can change suddenly. Given the complexities involved and all the variables that could change between now and then—whether in terms of technology, public policy, or prices—no long-term energy forecast will turn out to be right on the money. But sources like this Outlook are a great way to get a sense for what smart people in the energy industry see as they try to look ahead.

There is a tempting intuition to the idea that the real prices of non-renewable goods like coal, iron ore, or oil should rise, more or less, forever. It’s an easy argument to make, and it sounds right: The world’s population is getting bigger and bigger, so more and more goods like metals and hydrocarbons are being consumed. Every year, the sum total of what we’ve taken out of the ground mounts, never to be replaced. Supply of the stuff is limited—once it’s gone, it’s gone. So, this argument goes, as we exhaust our resources, we’ll have to mine, drill, or otherwise get our hands on it somehow but it will get more and more expensive to do so, because we’ll have exhausted the best stuff. Left to exploit ever-greater quantities of ever-more-marginal deposits, prices will rise indefinitely into the future. Thus, in this line of reasoning, unless we start consume less of a given non-renewable material, it will forever and ever get more expensive. The logic appears unimpeachable at first glance. But it’s wrong. The prices of raw materials have not traveled the path this story would predict for any traded commodity once inflation is factored in, over long stretches of time. One of the most powerfully counter-intuitive and empirically conclusive findings in economic history is that the real prices of nearly all major resources have actually trended lower over very long periods of time, even if they’re produced at higher and higher rates. (Oil, once OPEC got involved, is the glaring exception. But even oil prices since OPEC came about haven’t simply climbed higher and higher as global consumption has grown.) Though non-renewable commodity prices can rise steeply over years or even decades when supply and demand conditions warrant, over the centuries they’ve tended to decline after adjusted for inflation. The Economist industrial commodities index, first published in 1864, is widely considered to be the world’s oldest public, regularly updated price index. Though the nominal index stretches back to 1845, data before 1857 are incomplete and data between 1857 and 1861 reflect January prices only. Only figures from 1862 onwards,which represent averages of the underlying monthly figures, are used here. They are deflated using U.S. consumer price index data since 1871, which is used in the Case-Shiller historical home price index. (The message in the data is the same regardless of whether they are deflated by the U.S. consumer price index or the U.S. gross domestic product (GDP) deflator, as some prefer.) The industrial commodity index is a better reflection of long-term trends in non-renewable resource prices than the all-commodity index, which also includes food prices, so this analysis focuses on the former index. The commodities included in the industrials index, as well as their relative weightings, have changed over time, with the current weightings reflecting the value of world imports from 2004-2006. Figure 1. Economist Industrial-Commodity Price Index in Real and Nominal Terms (1871-2010) The trend is clear: Raw materials prices show a secular deterioration relative to manufactured goods over long stretches of time. Since 1871, the Economist industrial commodity-price index has sunk to roughly half its value in real terms, seeing average annual compound growth of -0.5% per year over the ensuing 140 years. Even after the boom years of the 2000s—in 2008, for instance, as commodity indexes soared, the Economist index never climbed more than halfway above where it stood 163 years earlier, in real terms. So, pessimists, rejoice: The future may be bleak, but it’s been bleaker.

The dramatic takeoff in oil and gas production in the United States and Canada over the last half decade has left many people asking whether a similar boom will happen in other countries. It’s a good question. To answer it, you have to start by identifying what critical factors enabled the boom to happen here, then figure out whether these same enabling factors exist elsewhere. Here’s a quick list of seven of these enablers. They vary in importance. Some are essential prerequisites to any shale production gains, like suitable geology. Others are catalysts: Without them, shale production is still possible, but will come much more slowly than it has in North America. The mineral rights regime is an example. Mineral rights regime: Land owners in the United States and Canada also own the subsurface rights to minerals found on their property. This is a highly unusual legal regime, but one that proved critical in launching the hydrocarbon boom by allowing landowners to negotiate directly with oil and gas companies for drilling rights. Of all the seven factors, this one was unquestionably one of the most important reasons why the boom has proceeded at the pace and volume that it has. Geology: The United States and Canada are blessed with some of the most prolific shale resources anywhere. Unless you’ve got the reserves, all the other ingredients won’t get you far.  Water supplies: Fracking is a water intensive process. Each well can require upwards of five million gallons of water, according to Platts, which are injected along with sand and other substances. Low population density: Unlike some other parts of the world, like the United Kingdom, much of North America’s shale reserves are located beneath places that are relatively sparsely populated. That extra elbow room means an easier operating environment for the industry and less headache for regulators. Deep capital markets: Financing small, risky drilling operations—the kind of undertakings required for an ultra-competitive upstream marketplace—are nothing new in this part of the world. Cutting-edge oil service companies: The technical capabilities that service companies like Halliburton offer have allowed new entrants to play in the shale space and even older operators to improve their metrics over time. Infrastructure: The U.S. oil and gas pipeline network, to name just one facet of the supply chain, is the most prolific in the world—and even it has been swamped by recent years’ output growth. Roads, rails, and other transportation infrastructure have been critical in allowing production to ramp up by linking wells to the marketplace. I’m sure there are others beyond the seven I’ve outlined here.  Anyone trying to project if or when shale production will get off the ground in a serious way beyond the United States and Canada will have to start by seeing whether the right conditions apply.

A team at Resources For the Future (RFF) led by Sheila Olmstead has a neat new paper in the Proceedings of the National Academy of Sciences (PNAS) that takes a rigorous look at water pollution due to shale gas development in Pennsylvania. (Hat tip: John Quigley.) The team collected thousands of data points measuring shale gas activity and water quality across a wide geographic area and more-than-ten-year span, and then used careful statistical analysis to test a series of hypotheses about how shale gas development might have affected water quality. What’s particularly interesting about this study is that it doesn’t require physical assumptions. It can also shed light on the cumulative impacts of large-scale shale gas development, going beyond analysis at the level of single pads and wells. The team’s conclusions are fairly straightforward. They find enhanced chlorine concentrations downstream of waste water treatment facilities but not downstream of drilling sites. Chlorine is a good marker of contamination from well flowback. What the RFF analysis suggests is that leaks or spills aren’t statistically detectable, at least at the watershed level, but that impacts of poorly processed wastewater are. That points to the value of focusing on wastewater treatment facilities if one wants to reduce the impact of chemical contamination resulting from shale gas development. The authors are clear to point out that Pennsylvania has made significant changes in the last couple years in how it handles wastewater; whether those are sufficient given the costs and benefits of additional controls remains to be seen. The RFF team also looks at “total suspended solids” (TSS) – essentially a fancy word for dirt. Here they find the reverse: no statistically detectable increase downstream from treatment facilities but now a non-trivial increase downstream from shale wells. The intuition makes sense: solids are readily removed by treatment facilities; solids displaced directly by shale gas activities, however, are not. But the paper also raises a puzzle. The most obvious way that shale development could increase TSS is through runoff from well pad construction. That should increase when it rains. But when the authors test for such a dynamic they can’t find it. They suggest other possibilities, such as road construction, as culprits. Further insight, though, will require more work. The study, likely any of this sort, has important acknowledged limitations. It doesn’t say anything about the prospect of future outlier events that might have ugly consequences. And it doesn’t really say anything about damages that are concentrated more narrowly than at the watershed level. Moreover, like any statistical study, it’s always possible that non-detection of damage reflects limitations on the dataset rather than a hard and fast reality. I’d also love to see the authors do some more estimates to put their results in the context of other influences on water quality, and in the context of the growing scale of shale development. Like I said, though, limits like these are inevitable. The RFF study is exactly the kind of work we need more of when it comes to the environmental impacts of shale development (and for that matter other activities too). One can only hope that regulators learn from the RFF results and that others continue to dig deeper into the issues they’ve raised.

I have a new note in the Journal of Geophysical Research (JGR) that I hope will be the last word in an increasingly tedious battle over an isolated but highly publicized methane leakage study that was published last year. I’ll explain what the note says in a moment, but first some background is in order. Last fall, JGR published my critique of a highly publicized study (also published in JGR) from a team at NOAA. The study had claimed massive leakage rates for methane from natural gas production. Methane is a potent warming gas; the results, if correct, were a bombshell. My critique was simple: the original study had made unsupportable assumptions; if you removed those and instead used more of the data that the NOAA team had collected, you found implied methane leakage rates far lower than what the NOAA team had estimated. No response from the original authors was published alongside my critique. This is unusual – it happened because the original authors did not submit a publishable response after being given half a year to do so. (My accepted paper was held from publication while JGR waited, which is normal, even if the waiting period was on the long side.) A couple months after my critique appeared, JGR published a NOAA-team response. The response claimed to a find fatal flaw in my paper and doubled down on their original claim that their data revealed methane leakage well above accepted estimates. Because the NOAA response had been accepted so late, I wasn’t given an opportunity to defend my paper at the time. Soon after, a similar team of researchers announced preliminary (pre-review) results from another study, claiming even more massive methane leakage in Utah. These once again attracted considerable attention. When I read the NOAA response in November, I was stunned. The supposed fatal flaw in my paper didn’t exist; the NOAA authors had conflated a math trick with a physical phenomenon and drawn conclusions from that. The NOAA authors did, however, argue that a data set that they had relied on in their paper, and that I had retained in mine (though with expressed concern), was shaky. They then used that to assert that my results weren’t to be trusted. What they didn’t mention was that if their data set was unreliable, then their own results had no foundation either. I quickly submitted a new note to JGR that made these points. It spent a couple months bouncing around in peer review because – and I find this kind of amazing – someone had found an additional flaw in the NOAA paper that I had not critiqued, and insisted that I needed to tackle it. My reply, including the additional requested critique (I swear I wasn’t trying to pick another fight), was finally accepted a few weeks ago. The paper in press is here for JGR subscribers; you can download a preprint here. In it, I defend my paper from one NOAA-team criticism, but accept that their critique of the data set (“flashing profiles”) that they introduced and relied on may be correct. I then explained the consequences of that for both their analysis and mine. Here’s my bottom line from the newest paper: “One can only conclude that either the flashing profiles are reasonably representative – in which case Petron et al [2012a] have presented no reason to question the results in Levi [2012] – or the flashing profiles are unrepresentative, in which case neither Petron et al. [2012] nor Levi [2012] have any basis to report reliable estimates of fugitive methane emissions. In either case, the results reported in Petron et al. [2012] are without foundation. Since the flashing profiles of condensate tanks in the area under study have likely changed since Petron et al. [2012] collected their data in 2008 (Petron et al [2012a]), this part of the debate is unlikely to be resolved definitively. Debate and observations should focus on rigorously understanding what is happening today through multiple observational and analytical methods. Several data collection efforts that could enable this are currently underway [EPA, 2012].” I hope that we can do just that: focus on serious measurements that are underway while putting this flawed study behind us.

As part of a book I’m working on, I’ve spent some time wading through the econometric literature on speculation in commodity markets, oil in particular. This body of research tries to shed light on how the inflow of investor money into commodity derivatives over the last decade has affected these markets. I’m skeptical of a lot of what’s out there on this topic, though there is also some excellent work, too, like from Bassam Fattouh at the Oxford Institute for Energy Studies. Unfortunately, much of the research on this topic doesn’t withstand close scrutiny. It’s not for a lack of smart people trying. I see it mainly as a data problem. The statistical methods used are often sophisticated, yes. But the publicly available data about global oil flows, including stockpiling, are far too limited, and not nearly internally consistent enough, to make it easy to form solid, actionable answers to many of the questions regulators have been trying to answer. It’s true that some research suggests changes in certain aspects of market behavior as the profile of market participants has evolved. Here’s an example. Jim Hamilton and Cynthia Wu made a compelling case in a working paper last year that risk premia in crude oil futures prices have changed since 2005, which they ascribe mainly to the inflow of financial-sector capital (see the figure below). Source: Hamilton and Wu, 2012 They may be right. But regulators should beware of drawing the wrong lessons from studies like this one. Fluctuations in risk premia are relevant to oil traders, but not necessarily relevant to normal people, whose focus is on how much they pay at the pump. A change in one aspect of the market (in this case, derivative risk premia) does not necessarily cause a problematic or unfair change in other aspects, like retail prices. Yes, the two can at times be linked, but not always. Sensible regulation in commodity markets doesn’t seek to impose stasis on what should be a dynamic, evolving market, but rather to respond to structural changes that undermine the utility of these markets, their function as a means of price discovery, and their role in the economy more broadly.