Policy – Page 7

Stop talking, start studying?

Roger Pielke Jr. poses a carbon price paradox:

The carbon price paradox is that any politically conceivable price on carbon can do little more than have a marginal effect on the modern energy economy. A price that would be high enough to induce transformational change is just not in the cards. Thus, carbon pricing alone cannot lead to a transformation of the energy economy.

Put another way:

Advocates for a response to climate change based on increasing the costs of carbon-based energy skate around the fact that people react very negatively to higher prices by promising that action won’t really cost that much. … If action on climate change is indeed “not costly” then it would logically follow the only reasons for anyone to question a strategy based on increasing the costs of energy are complete ignorance and/or a crass willingness to destroy the planet for private gain. … There is another view. Specifically that the current ranges of actions at the forefront of the climate debate focused on putting a price on carbon in order to motivate action are misguided and cannot succeed. This argument goes as follows: In order for action to occur costs must be significant enough to change incentives and thus behavior. Without the sugarcoating, pricing carbon (whether via cap-and-trade or a direct tax) is designed to be costly. In this basic principle lies the seed of failure. Policy makers will do (and have done) everything they can to avoid imposing higher costs of energy on their constituents via dodgy offsets, overly generous allowances, safety valves, hot air, and whatever other gimmick they can come up with.

His prescription (and that of the Breakthrough Institute) is low carbon taxes, reinvested in R&D:

We believe that soon-to-be-president Obama’s proposal to spend $150 billion over the next 10 years on developing carbon-free energy technologies and infrastructure is the right first step. … a $5 charge on each ton of carbon dioxide produced in the use of fossil fuel energy would raise $30 billion a year. This is more than enough to finance the Obama plan twice over.

… We would like to create the conditions for a virtuous cycle, whereby a small, politically acceptable charge for the use of carbon emitting energy, is used to invest immediately in the development and subsequent deployment of technologies that will accelerate the decarbonization of the U.S. economy.

…

Stop talking, start solving

As the nation begins to rely less and less on fossil fuels, the political atmosphere will be more favorable to gradually raising the charge on carbon, as it will have less of an impact on businesses and consumers, this in turn will ensure that there is a steady, perhaps even growing source of funds to support a process of continuous technological innovation.

This approach reminds me of an old joke:

Lenin, Stalin, Khrushchev and Brezhnev are travelling together on a train. Unexpectedly the train stops. Lenin suggests: “Perhaps, we should call a subbotnik, so that workers and peasants fix the problem.” Kruschev suggests rehabilitating the engineers, and leaves for a while, but nothing happens. Stalin, fed up, steps out to intervene. Rifle shots are heard, but when he returns there is still no motion. Brezhnev reaches over, pulls the curtain, and says, “Comrades, let’s pretend we’re moving.”

I translate the structure of Pielke’s argument like this:

Pielke Loops

Implementation of a high emissions price now would be undone politically (B1). A low emissions price triggers a virtuous cycle (R), as revenue reinvested in technology lowers the cost of future mitigation, minimizing public outcry and enabling the emissions price to go up. Note that this structure implies two other balancing loops (B2 & B3) that serve to weaken the R&D effect, because revenues fall as emissions fall.

If you elaborate on the diagram a bit, you can see why the technology-led strategy is unlikely to work:

First, there’s a huge delay between R&D investment and emergence of deployable technology (green stock-flow chain). R&D funded now by an emissions price could take decades to emerge. Second, there’s another huge delay from the slow turnover of the existing capital stock (purple) – even if we had cars that ran on water tomorrow, it would take 15 years or more to turn over the fleet. Buildings and infrastructure last much longer. Together, those delays greatly weaken the near-term effect of R&D on emissions, and therefore also prevent the virtuous cycle of reduced public outcry due to greater opportunities from getting going. As long as emissions prices remain low, the accumulation of commitments to high-emissions capital grows, increasing public resistance to a later change in direction. Continue reading “Stop talking, start studying?”

Are causal loop diagrams useful?

Reflecting on the Afghanistan counterinsurgency diagram in the NYTimes, Scott Johnson asked me whether I found causal loop diagrams (CLDs) to be useful. Some system dynamics hardliners don’t like them, and others use them routinely.

Here’s a CLD:

Chicken CLD

And here’s it’s stock-flow sibling:

Chicken Stock Flow

My bottom line is:

CLDs are very useful, if developed and presented with a little care.
It’s often clearer to use a hybrid diagram that includes stock-flow “main chains”. However, that also involves a higher burden of explanation of the visual language.
You can get into a lot of trouble if you try to mentally simulate the dynamics of a complex CLD, because they’re so underspecified (but you might be better off than talking, or making lists).
You’re more likely to know what you’re talking about if you go through the process of building a model.
A big, messy picture of a whole problem space can be a nice complement to a focused, high quality model.

Here’s why:

Continue reading “Are causal loop diagrams useful?”

Another look at inadequate Copenhagen pledges

Joeri Rogelj and others argue that Copenhagen Accord pledges are paltry in a Nature Opinion,

Current national emissions targets can’t limit global warming to 2 °C, calculate Joeri Rogelj, Malte Meinshausen and colleagues — they might even lock the world into exceeding 3 °C warming.

Nations will probably meet only the lower ends of their emissions pledges in the absence of a binding international agreement

Nations can bank an estimated 12 gigatonnes of Co2 equivalents surplus allowances for use after 2012

Land-use rules are likely to result in further allowance increases of 0.5 GtCO2-eq per year

Global emissions in 2020 could thus be up to 20% higher than today

Current pledges mean a greater than 50% chance that warming will exceed 3°C by 2100

If nations agree to halve emissions by 2050, there is still a 50% chance that warming will exceed 2°C and will almost certainly exceed 1.5°C

Via Nature’s Climate Feedback, Copenhagen Accord – missing the mark.

Computer models running the EU? Eruptions, models, and clueless reporting

The EU airspace shutdown provides yet another example of ignorance of the role of models in policy:

Computer Models Ruining EU?

Flawed computer models may have exaggerated the effects of an Icelandic volcano eruption that has grounded tens of thousands of flights, stranded hundreds of thousands of passengers and cost businesses hundreds of millions of euros. The computer models that guided decisions to impose a no-fly zone across most of Europe in recent days are based on incomplete science and limited data, according to European officials. As a result, they may have over-stated the risks to the public, needlessly grounding flights and damaging businesses. “It is a black box in certain areas,” Matthias Ruete, the EU’s director-general for mobility and transport, said on Monday, noting that many of the assumptions in the computer models were not backed by scientific evidence. European authorities were not sure about scientific questions, such as what concentration of ash was hazardous for jet engines, or at what rate ash fell from the sky, Mr. Ruete said. “It’s one of the elements where, as far as I know, we’re not quite clear about it,” he admitted. He also noted that early results of the 40-odd test flights conducted over the weekend by European airlines, such as KLM and Air France, suggested that the risk was less than the computer models had indicated. – Financial Times

Calculators of the global climate deal, unite!

Read all about it at Climate Interactive.

One child at the crossroads

China’s one child policy is at its 30th birthday. Inside-Out China has a quick post on the debate over the future of the policy. That caught my interest, because I’ve seen recent headlines calling for an increase in China’s population growth to facilitate dealing with an aging population – a potentially disastrous policy that nevertheless has adherents in many countries, including the US.

Here are the age structures of some major countries, young and old:

population structure

Vertical axis indicates the fraction of the population that resides in each age category.

Germany and Japan have the pig-in-the-python shape that results from falling birthrates. The US has a flatter age structure, presumably due to a combination of births and immigration. Brazil and India have very young populations, with the mode at the left hand side. Given the delay between birth and fertility, that builds in a lot of future growth.

Compared to Germany and Japan, China hardly seems to be on the verge of an aging crisis. In any case, given the bathtub delay between birth and maturity, a baby boom wouldn’t improve the dependency ratio for almost two decades.

More importantly, growth is not a sustainable strategy for coping with aging. At the same time that growth augments labor, it dilutes the resource base and capital available per capita. If you believe that people are the ultimate resource, i.e. that increasing returns to human capital will create offsetting technical opportunities, that might work. I rather doubt that’s a viable strategy though; human capital is more than just warm bodies (of which there’s no shortage); it’s educated and productive bodies – which are harder to get. More likely, a growth strategy just accelerates the arrival of resource constraints. In any case, the population growth play is not robust to uncertainty about future returns to human capital – if there are bumps on the technical road, it’s disastrous.

To say that population growth is a bad strategy for China is not necessarily to say that the one child policy should stay. If its enforcement is spotty, perhaps lifting it would be a good thing. Focusing on incentives and values that internalize population tradeoffs might lead to a better long term outcome than top-down control.

Painting ourselves into a green corner

At the Green California Summit & Expo this week, I saw a strange sight: a group of greentech manufacturers hanging out in the halls, griping about environmental regulations. Their point? That a surfeit of command-and-control measures makes compliance such a lengthy and costly process that it’s hard to bring innovations to market. That’s a nice self-defeating outcome!

Consider this situation:

greenCorner
I was thinking of lighting, but it could be anything. Letters a-e represent technologies with different properties. The red area is banned as too toxic. The blue area is banned as too inefficient. That leaves only technology a. Maybe that’s OK, but what if a is made in Cuba, or emits harmful radiation, or doesn’t work in cold weather? That’s how regulations get really complicated and laden with exceptions. Also, if we revise our understanding of toxics, how should we update this to reflect the tradeoffs between toxics in the bulb and toxics from power generation, or using less toxic material per bulb vs. using fewer bulbs? Notice that the only feasible option here – a – is not even on the efficient frontier; a mix of e and b could provide the same light with slightly less power and toxics.

Proliferation of standards creates a situation with high compliance costs, both for manufacturers and the bureaucracy that has to administer them. That discourages small startups, leaving the market for large firms, which in turn creates the temptation for the incumbents to influence the regulations in self-serving ways. There are also big coverage issues: standards have to be defined clearly, which usually means that there are fringe applications that escape regulation. Refrigerators get covered by Energy Star, but undercounter icemakers and other cold energy hogs don’t. Even when the standards work, lack of a price signal means that some of their gains get eaten up by rebound effects. When technology moves on, today’s seemingly sensible standard becomes part of tomorrow’s “dumb laws” chain email.

The solution is obviously not total laissez faire; then the environmental goals just don’t get met. There probably are some things that are most efficient to ban outright (but not the bulb), but for most things it would be better to impose upstream prices on the problems – mercury, bisphenol A, carbon, or whatever – and let the market sort it out. Then providers can make tradeoffs the way they usually do – which package of options makes the cheapest product? -without a bunch of compliance risk involved in bringing their product to market.

Here’s the alternative scheme:

greenTradeoffs

The green and orange lines represent isocost curves for two different sets of energy and toxic prices. If the unit prices of a-e were otherwise the same, you’d choose b with the green pricing scheme (cheap toxics, expensive energy) and e in the opposite circumstance (orange). If some of the technologies are uniquely valuable in some situations, pricing also permits that tradeoff – perhaps c is not especially efficient or clean, but has important medical applications.

With a system driven by prices and values, we could have very simple conversations about adaptive environmental control. Are NOx levels acceptable? If not, raise the price of emitting NOx until it is. End of discussion.

Two related tidbits:

Fed green buildings guru Kevin Kampschroer gave an interesting talk on the GSA’s greening efforts. He expressed hope that we could move from LEED (checklists) to LEEP (performance-based ratings).

I heard from a lighting manufacturer that the cost of making a CFL is under a buck, but running a recycling program (for mercury recapture) costs $1.50/bulb. There must be a lot of markup in the distribution channels to get them up to retail prices.

The lure of border carbon adjustments

Are border carbon adjustments (BCAs) the wave of the future? Consider these two figures:

The first shows the scale of carbon embodied in trade. The second, even if it overstates true intentions, demonstrates the threat of carbon outsourcing. Both are compelling arguments for border adjustments (i.e. tariffs) on GHG emissions.

I think things could easily go this route: it’s essentially a noncooperative route to a harmonized global carbon price. Unlike global emissions trading, it’s not driven by any principle of fair allocation of property rights in the atmosphere; instead it serves the more vulgar notion that everyone (or at least every nation) keeps their own money.

Consider the pros and cons:

Advocates of BCAs claim that the measures are intended to address three factors. First, competitiveness concerns where some industries in developed countries consider that a BCA will protect their global competitiveness vis-a-vis industries in countries that do not apply the same requirements. The second argument for BCAs is ‘carbon leakage’ – the notion that emissions might move to countries where rules are less stringent. A third argument, of the highest political relevance, has to do with ‘leveraging’ the participation of developing countries in binding mitigation schemes or to adopt comparable measures to offset emissions by their own industries.

from a developing country perspective, at least three arguments run counter to that idea: 1) that the use of BCAs is a prima facie violation of the spirit and letter of multilateral trade principles and norms that require equal treatment among equal goods; 2) that BCAs are a disguised form of protectionism; and 3) that BCAs undermine in practice the principle of common but differentiated responsibilities.

In other words: the advocates are a strong domestic constituency with material arguments in places where BCAs might arise. The opponents are somewhere else and don’t get to vote, and armed with legalistic principles more than fear and greed.

Fuzzy VISION

Like spreadsheets, open-loop models are popular but flawed tools. An open loop model is essentially a scenario-specification tool. It translates user input into outcomes, without any intervening dynamics. These are common in public discourse. An example turned up in the very first link when I googled “regional growth forecast”:

The growth forecast is completed in two stages. During the first stage SANDAG staff produces a forecast for the entire San Diego region, called the regionwide forecast. This regionwide forecast does not include any land use constraints, but simply projects growth based on existing demographic and economic trends such as fertility rates, mortality rates, domestic migration, international migration, and economic prosperity.

In other words, there’s unidirectional causality from inputs to outputs, ignoring the possible effects of the outputs (like prosperity) on the inputs (like migration). Sometimes such scenarios are useful as a starting point for thinking about a problem. However, with no estimate of the likelihood of realization of such a scenario, no understanding of the feedback that would determine the outcome, and no guidance about policy levers that could be used to shape the future, such forecasts won’t get you very far (but they might get you pretty deep – in trouble).

The key question for any policy, is “how do you get there from here?” Models can help answer such questions. In California, one key part of the low-carbon fuel standard (LCFS) analysis was VISION-CA. I wondered what was in it, so I took it apart to see. The short answer is that it’s an open-loop model that demonstrates a physically-feasible path to compliance, but leaves the user wondering what combination of vehicle and fuel prices and other incentives would actually get consumers and producers to take that path.

First, it’s laudable that the model is publicly available for critique, and includes macros that permit replication of key results. That puts it ahead of most analyses right away. Unfortunately, it’s a spreadsheet, which makes it tough to know what’s going on inside.

I translated some of the model core to Vensim for clarity. Here’s the structure:

VISION-CA

Bringing the structure into the light reveals that it’s basically a causal tree – from vehicle sales, fuel efficiency, fuel shares, and fuel intensity to emissions. There is one pair of minor feedback loops, concerning the aging of the fleet and vehicle losses. So, this is a vehicle accounting tool that can tell you the consequences of a particular pattern of new vehicle and fuel sales. That’s already a lot of useful information. In particular, it enforces some reality on scenarios, because it imposes the fleet turnover constraint, which imposes a delay in implementation from the time it takes for the vehicle capital stock to adjust. No overnight miracles allowed.

What it doesn’t tell you is whether a particular measure, like an LCFS, can achieve the desired fleet and fuel trajectory with plausible prices and other conditions. It also can’t help you to decide whether an LCFS, emissions tax, or performance mandate is the better policy. That’s because there’s no consumer choice linking vehicle and fuel cost and performance, consumer knowledge, supplier portfolios, and technology to fuel and vehicle sales. Since equilibrium analysis suggests that there could be problems for the LCFS, and disequilibrium generally makes things harder rather than easier, those omissions are problematic.

Continue reading “Fuzzy VISION”

Category: Policy