What Back To The Future Day says about scenario development

As many, many websites show, Back To The Future II got a few things right - and many things wrong. What I find most intriguing is not so much the stuff the movie projected into 2015 but failed to materialize (hoverboards, flying cars), as what the movie did not see coming (notably, the replacement of fax machines by the Internet). But it's easy to ridicule such projections with what we know now - and let's not forget it was an entertainment movie, not an academic study in futurology.

What's more, if only Elsevier had waited one day, our VECTORS scenario paper would have been made available online exactly on the day Marty McFly arrives in the future! Actually, Back To The Future II is a perfect illustration of the merits and limits of scenario studies. When we developed the VECTORS scenarios I heard many responses like "it's science fiction", "we don't know what the future will be like", and so on. And it's true: we don't know what the future will be like, which is why you want to develop several scenarios in order to explore the bandwidth of possible outcomes. The variation in scenarios is more important than any (misguided) notion of accuracy or likelihood. In fact, it is better to ditch likelihood altogether and settle for 'plausibility'. As we describe in the paper, this turned out to be a difficult thing for academics as you need to get out of your ivory comfort zone and speculate.

The reason I find the fax machines in the movie intriguing is that it shows how we tend to extrapolate current trends into the future: fax machines were becoming ubiquitous around 1980, just when the movie was made. So we can't blame the movie makers for extrapolating that trend into a future where just about every street corner would have a fax machine. But then, what else can we do? Of course there are dangers to extrapolation, especially if you have good reasons to assume that a given trend will not hold outside your range of observations. Nevertheless, no matter how plausible (and probable) your extrapolation, the probability that it comes true exactly as you estimated is precisely zero. Again: it is the variation around that extrapolation that is much more interesting than the extrapolation itself.

Meet my new band

I've joined a new band: we're called Tobermore, we're mostly Dutch (our uillean piper is half Irish, half Flemish, and makes great chocolates), and we play Irish traditional music with the occasional Americana song.

Although I joined them only a few months ago, this actually started somewhere in 2009-2010 when I stood in for the guitarist of another group, Harmony Glen. I got along quite well with their then box player, Vincent, and Vincent and I formed a duo playing Dutch music, Hete Bliksem (yes I know the link is broken - the website is still under construction - as is the band). After a couple of years, Vincent left Harmony Glen, and joined Tobermore; when they asked me to join them as fiddler I did not need long to consider their invitation. They're great musicians and, most importantly, great company.

My interest in folk music started with, as for so many people, The Pogues. There was a time when I would go to Ireland every year, first with my guitar, then with my bódhran, then with my mandolin. Visiting the Saint Chartier Festival in 2000 changed many things in my life, not least of all my musical focus: I bought a fiddle and immersed myself in bal folk music. I still play bal folk, mostly with old Dutch tunes, but I'm also happy to be back in Irish music again.

Why (not) price nature?

A few remarks on today's debate on economic valuation of ecosystem services, here in Wageningen:

• Having two non-economists as the only speakers in a debate on economic valuation of ecosystem services led to the usual misconceptions of economics, some if which I will explain below.
• I have written most of what I can say about the issue in this post.
• In my three-species typology in that post, Dolf de Groot is a typical pragmatic ecologist: he literally called valuation "a necessary evil."
• The same typology might label Bram Büscher (a sociologist) a hardcore ecologist, but actually his arguments were more of a Marxist critique of economics and capitalism than of a moral nature (intrinsic value 'n all). In short his argument is that ecosystem degradation is caused by the logic of capitalism; pricing nature perpetuates that logic rather than abolishing it.
• De Groot claimed that "conventional economists ignore most externalities, like ecosystem degradation." As a conventional environmental economist, who has been working on nothing else for the past ten years than externalities and other market failures, and who meets hundreds of similar economists every year at the meetings of EAERE, AERE, IIFET, BIOECON, and so on, I found this very strange to hear, to put it mildly.
• Another statement by De Groot was that unlike pricing, valuing "is not about substitution." Economic valuation is ALWAYS about substitution. If you don't like the idea that people can be compensated for ecological degradation, don't do valuation. De Groot wants to have his cake and eat it too.
• It is a more general problem I have with the so-called 'ecological economists': a lot of their valuation work is poorly thought through, poorly executed, and done from a political agenda rather than out of scientific curiosity.
• Common mistakes by ecological economists are (1) not properly defining what they measure (like doing a stated preference survey among tourists to measure indirect use values); (2) aggregating values to such a scale that prices are bound to change (the most fundamental critique of Costanza et al.'s 1997 paper); (3) treating economic values like they would treat biophysical variables such as temperature or density (which are not context-dependent while economic value depends on what question you are asking).
• Büscher repeated the Suzuki fallacy that "externality" means "not part of the economic system"
• Büscher "did not have time" to propose an alternative to the capitalist system. Perhaps he should have a look at the historical alternatives to capitalism and their wonderful impact on the environment.
• Büscher quoted a Chinese philosopher (probably Sun Tzu) that "if you can get your enemy to speak your language you have won the battle" or something in that spirit. I don't agree. Economists study the rules of market allocation (property rights, taxation, and so on) to understand where such rules work and where they don't. This would suggest that our advice would always favour big business. But being market-friendly is not the same as being business-friendly.
• I'm in favour of pricing ecosystem services, but only in the context of concrete policy decisions, in a proper cost-benefit analysis that is part of a wider policy-making process that also takes into account other considerations besides economic value (such as intrinsic value, distribution of effects, and so on). Don't try to estimate the total value of the planet, as Costanza did.

Programming languages compared, and why I'm sticking with Python until Julia grows up

Comparisons of programming languages abound, especially with regard to running speed. This paper in the Journal of Economic Dynamics and Control by Boragan Aruoba of the University of Maryland and Jesús Fernández-Villaverde of the University of Pennsylvania is yet another one, albeit in a peer-reviewed journal and with a procedure (value function iteration) that is common in my field. Main observations:

• When it comes to speed nothing beats C++ and FORTRAN.
• Julia performs really well: only 2.37 times the running time of C++.
• Python and R are slowpokes, at about 45 (Python with the Pypy interpreter) to 491 times (R without its Compiler package) times the running time of C++.
• Matlab is somewhat inbetween the slowpokes and the frontrunners, with about 9 times the running time of C++.
• R, Matlab and Python can get a boost from just-in-time-compilers and C compilers (like Rcpp for R; or Numba or Cython for Python) that make their running time comparable to that of Julia (although Rcpp is still a bit disappointing: 5.4 times the C++ running time).

Adding my own considerations:

• I tried C++ and gave up very quickly. I bloody hate it with a passion.
• I find R not much better: even though it is a scripted language it is clumsy, illogical, and makes for horrible code. Rcpp worked fine until I found out that it cannot handle matrices with more than 2 dimensions. Speeding up your R code with bigger matrices requires the use of full-blown C++. In other words, two languages that I bloody hate.
• I value my independence, so I prefer to work on my own laptop with my own licenses. That makes Matlab, with its steep license fee, a no-go.
• I've experimented with Cython and it seems to work quite well. I love the accessibility and clear layout of Python; moreover, my university teaches Python twice a year in an undergrad course. The only real problem with Python is that it is reputedly difficult to parallellize.
• One day I'll start using Julia. It's fast, accessible, and (so they say) easy to parallellize. But not until there is a stable version and a decent IDE.

On interdisciplinarity

Check out the really cool cover of Nature's special feature on interdisciplinarity!

Of course, as an economist I especially like their inclusion of "Invisible Hand" as the sole superhero representing the social sciences in their scientific team of Avengers. But it is also symbolic for the fact that economists have, in my view, gone the furthest in integrating their discipline with the natural sciences. This holds particularly for environmental and resource economists, who by definition deal with problems of the natural environment like pollution and overfishing. The reason is pretty geeky: most economic research is quantitative, and quite a lot involves the development of mathematical models. And whaddayaknow: so do climate science, population biology, hydrology, and a host of other natural sciences. Give me your equations and I'll plug them into my CGE model.

It is actually much, much harder to truly integrate qualitative social sciences like sociology or anthropology with quantitative sciences - even with a social science like economics. Models like IMAGE and DICE describe the global climate as well as the economy; the Gordon-Schaefer fisheries model and Colin Clark's work on renewable resource use, which use basic models from population biology like logistic growth, are part of the standard canon of resource economics since decades; when Daniel Pauly criticizes the limited impact of the "social sciences" on fisheries research, he lumps together economics with biology, not sociology. Meanwhile, it has taken until 2009 that the Nobel committee finally recognized anthropologist Elinor Ostrom for her contributions to the economics of common pool resources, and economists and sociologists share little but contempt for each others' fields. The Indian economist Jagdish Bhagwati is said to have joked that good economists reincarnate as physicists; wicked economists reincarnate as sociologists. But Ostrom's Nobel also shows that things are changing, especially in the field of institutional economics. Let's have more of that in the future.

OMICS Publishing Group clogs my inbox

Just got the third invitation in a month to review a paper on marine microbiology. Looking up the publisher I found this. Little wonder my reply to them was a tad less polite than the previous two:

1. I'm a natural resource economist with no knowledge of biology.
2. This is the third such invitation. You're wasting your time and, worse, mine.
3. You're on a list of predatory publishers: http://scholarlyoa.com/2013/01/25/omics-predatory-meetings/ 

Stop wasting my time. I will now block your e-mails from my account.

Science on marine plastic debris

Science just published an excellent article on the problem of marine plastic debris. Its main conclusion is that

"275 million metric tons (MT) of plastic waste was generated in 192 coastal countries in 2010, with 4.8 to 12.7 million MT entering the ocean."

The authors break this number down by country, and show that four Asian countries (China, Indonesia, Philippines, Vietnam) contribute almost half the plastic waste going into the oceans. The US is 20^th in rank, contributing 0.9%; the authors also explain that the EU would be 18^th in rank if it were counted as one country, which implies that the EU also contributes about 1% to the total amount of plastic waste going into the oceans. A few more observations:

• The list is dominated by middle-income countries. The only low-income countries are Bangladesh, Burma, and North Korea. Is this the environmental Kuznets at work?
• There is a striking correlation between income and the quality of waste management. The countries with the highest percentage of mismanaged waste are low-income countries or lower-middle-income countries. Even upper-middle-income countries have rates between 50% and 80%.
• Brazil and Turkey are intriguing exceptions: despite being upper-middle-income countries their mismanagement rates are 11% and 18%, respectively. What are these countries doing differently than the rest?
• The US has a comparatively low mismanagement rate (2%), but compensates its effort by the sheer amount of plastics produced per capita: 2.58 kg, where most other countries range between 0.5 and 1.5 kg. EU figures are not given but I suspect the EU does worse on waste treatment than the US.
• A notable exception to that observation is Sri Lanka with a whopping 5.1 kg plastic waste produced per capita. What do they need all that plastic for?

Overall I can't help but thinking that the energy invested by well-meaning westerners to reduce their use of plastics is but a drop in the ocean as long as the emerging world does not clean up its act.

Associate professor

I just realised that I never announced on this blog that I presented my (new and improved) research vision to the assessment committee for a second time - and that the assessment committee agreed that I should be appointed associate professor as of 1 November 2014.

So there you go: as of 1 November 2014 I am in the position of associate professor.

(Fireworks, music, ticker tape.)

I would have liked to say that my trip to Australia inspired the main research focus I put into my research vision: to develop computational models of coastal and marine resource use, drawing on experiences from other economics subdisciplines such as macroeconomics. But honestly, it's the other way around: I went there to learn more about computational models because I believe they can be useful. But it was good to talk to my peers in the field and realise that it's actually not so bad an idea. You can find the vision document here, and the presentation here.

I still feel more or less the same about the tenure track system as I did last time: it's a good concept although its application in Wageningen University has its teething problems.

As for any advice I can give other people on the tenure track, I'm not sure whether my advice is worth anything but I can at least give you my opinion:

• Expose your ideas to your peers. We don't have a mentor system in Wageningen (we should!!), neither do we have many staff who have been through the tenure track themselves. So the next best thing is to go out, talk to other academic researchers, and try to learn from them as much as you can. Have a beer with them at a conference. Try to arrange a sabbatical at their university. Try to get them to your own university for a seminar or a PhD defence. Send them your written research vision and ask them what they think.
• Set your own goals. Yes I know you have 18 criteria to meet (I kid you not), but first and foremost you must decide which direction you want to go - and then go there within whatever limits are set by the official criteria.

For what it's worth.