Enabling an R&D addiction

I actually mean that in a good way. A society addicted to learning and innovation would be pretty cool.

However, it’s not all about money. Quoting the OSTP Science of Science Policy Roadmap,

Investment in science and technology, however, is only one of the policy instruments available to science policy makers; others include fostering the role of competiton and openness in the promotion of discovery, the construction of intellectual property systems, tax policy, and investment in a STEM workforce. However, the probable impact of these various policies and interventions is largely unknown. This lack of knowledge can lead to serious and unintended consequences.

In other words, to spend $16 billion/year wisely, you have to get a number of moving parts coordinated, including:

  1. Prices & tax policy. If prices of natural resources, national security, clean air, health, etc. don’t reflect their true values to society, innovation policy will be pushing against the tide. Innovations will be DOA in the marketplace. The need for markets for products is matched by the need for markets for innovators:
  2. Workforce management. Just throwing money at a problem can create big dislocations in researcher demographics. Put it all into academic research, and you create a big glut of graduates who have no viable career path in science. Put it all into higher education, and your pipeline of talent will be starved by poor science preparation at lower levels. Put it all into labs and industry, and it’ll turn into pay raises for a finite pool of workers. Balance is needed.
  3. Intellectual property law. This needs to reflect the right mix of incentives for private investment and recognition that creations are only possible to the extent that we stand on the shoulders of giants and live in a society with rule of law. Currently I suspect that law has swung too far toward eternal protection that actually hinders innovation.

At the end of the day, #1 is most important. Regardless of the productivity of the science enterprise, someone will probably figure out how to make graphene cables or an aspen tree that bears tomatoes. The key question, then, is how society puts those things to use, to solve its problems and improve welfare. That requires a delicate balancing act, between preserving diversity and individual freedom to explore new ways of doing things, and preventing externalities from harming everyone else.

R&D – crack for techno-optimists

I like R&D. Heck, I basically do R&D. But the common argument, that people won’t do anything hard to mitigate emissions or reduce energy use, so we need lots of R&D to find solutions, strikes me as delusional.

The latest example to cross my desk (via the NYT) is the new American Energy Innovation Council’s recommendations,

Create an independent national energy strategy board.
Invest $16 billion per year in clean energy innovation.
Create Centers of Excellence with strong domain expertise.
Fund ARPA-E at $1 billion per year.
Establish and fund a New Energy Challenge Program to build large-scale pilot projects.

Let’s look at the meat of this – $16 billion per year in energy innovation funding. Historic funding looks like this:

R&D funding

Total public energy R&D, compiled from Gallagher, K.S., Sagar, A, Segal, D, de Sa, P, and John P. Holdren, “DOE Budget Authority for Energy Research, Development, and Demonstration Database,” Energy Technology Innovation Project, John F. Kennedy School of Government, Harvard University, 2007. I have a longer series somewhere, but no time to dig it up. Basically, spending was negligible (or not separately accounted for) before WWII, and ramped up rapidly after 1973.

The data above reflects public R&D; when you consider private spending, the jump to $16 billion represents maybe a factor of 3 or 4 increase. What does that do for you?

Consider a typical model of technical progress, the two-factor learning curve:

cost = (cumulative R&D)^A*(cumulative experience)^B

The A factor represents improvement from deliberate R&D, while the B factor reflects improvement from production experience like construction and installation of wind turbines. A and B are often expressed as learning rates, the multiple on cost that occurs per doubling of the relevant cumulative input. In other words, A,B = ln(learning rate)/ln(2). Typical learning rates reported are .6 to .95, or cost reductions of 40% to 5% per doubling, corresponding with A/B values of -.7 to -.15, respectively. Most learning rate estimates are on the high end (smaller reductions per doubling), particularly when the two-factor function is used (as opposed to just one component).

Let’s simplify so that

cost = (cumulative R&D)^A

and use an aggressive R&D learning rate (.7), for A=-0.5. In steady state, with R&D growing at the growth rate of the economy (call it g), cost falls at the rate A*g (because the integral of exponentially growing spending grows at the same rate, and exp(g*t)^A = exp(A*g*t)).

That’s insight number one: a change in R&D allocation has no effect on the steady-state rate of progress in cost. Obviously one could formulate alternative models of technology where that is not true, but compelling argument for this sort of relationship is that the per capita growth rate of GDP has been steady for over 250 years. A technology model with a stronger steady-state spending->cost relationship would grow super-exponentially.

Insight number two is what the multiple in spending (call it M) does get you: a shift in the steady-state growth trajectory to a new, lower-cost path, by M^A. So, for our aggressive parameter, a multiple of 4 as proposed reduces steady-state costs by a factor of about 2. That’s good, but not good enough to make solar compatible with baseload coal electric power soon.

Given historic cumulative public R&D, 3%/year baseline growth in spending, a 0.8 learning rate (a little less aggressive), a quadrupling of R&D spending today produces cost improvements like this:

R&D future 4x

Those are helpful, but not radical. In addition, even if R&D produces something more miraculous than it has historically, there are still big nontechnical lock-in humps to overcome (infrastructure, habits, …). Overcoming those humps is a matter of deployment more than research. The Energy Innovation Council is definitely enthusiastic about deployment, but without internalizing the externalities associated with energy production and use, how is that going to work? You’d either need someone to pick winners and implement them with a mishmash of credits and subsidies, or you’d have to hope for/wait for cleantech solutions to exceed the performance of conventional alternatives.

The latter approach is the “stone age didn’t end because we ran out of stones” argument. It says that cleantech (iron) will only beat conventional (stone) when it’s unequivocally better, not just for the environment, but also convenience, cost, etc. What does that say about the prospects for CCS, which is inherently (thermodynamically) inferior to combustion without capture? The reality is that cleantech is already better, if you account for the social costs associated with energy. If people aren’t willing to internalize those social costs, so be it, but let’s not pretend we’re sure that there’s a magic technical bullet that will yield a good outcome in spite of the resulting perverse incentives.

Gallagher, K.S., Sagar, A, Segal, D, de Sa, P, and John P. Holdren, “DOE Budget Authority for Energy Research, Development, and Demonstration Database,” Energy Technology Innovation Project, John F. Kennedy School of Government, Harvard University, 2007.

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?”

Endogenous Energy Technology

I just created an annotated list of links on learning/experience curves, deliberate R&D, and other forms of endogenous energy technology, including a few models and empirical estimates. See del.icio.us/tomfid for details. Comments with more references will be greatly appreciated!