According to google searches and news, since 2008 the news has been writing much more about crisis, but people haven’t been searching for it so much.
a search for financial crisis and euro crisis leads to a more striking result.
This critical question relates to a suite of resilience related research fields, ranging from early warnings of catastrophic shifts in ecosystems, non-linear planetary boundaries, and the role of perceived crisis as triggers of transformations towards more adaptive forms of ecosystem governance.
The answer might seem quite straight-forward: “yes!”. Why wouldn’t political actors try to steer away from potentially devastating tipping points? Political philosopher Stephen M. Gardiner elaborates the opposite position in a very thought-provoking article in the Journal of Social Philosophy (2009) about the moral implications of abrupt climate change.
According to Gardiner, several economical, psychological and intergenerational dilemmas make it likely that an increased awareness of devastating “tipping points”, undermine political actors’ work towards effective climate change mitigation. Instead, it induces them to focus on adaptation measures, and involve in what Gardiner denotes an “Intergenerational Arms Race”.
Suppose, for example, that a given generation knew that it would be hit with a catastrophic abrupt change no matter what it did. Might it not be inclined to fatalism? If so, then the temporal proximity of abrupt change would actually enhance political inertia, rather than undercut it. (Why bother?)
In addition, according to Gardiner, in facing abrupt climate change, there will be other more urgent concerns than climate change mitigation, again creating greater risks for future generations.
[T]he proximity of the abrupt change may actually provide an incentive for increasing current emissions above the amount that even a completely self-interested generation would normally choose. What I have in mind is this. Suppose that a generation could increase its own ability to cope with an impending abrupt change by increasing its emissions beyond their existing level. (For example, suppose that it could boost economic output to enhance adaptation efforts by relaxing existing emissions standards.) Then, it would have a generation-relative reason to do so, and it would have this even if the net costs of the additional emissions to future generations far exceed the short-term benefits. Given this, it is conceivable that the impending presence of a given abrupt change may actually exacerbate the PIBP “the problem of intergenerational buck passing”], leaving future generations worse off than under the gradualist paradigm.
So what are the ways to get out of this dilemma? Gardiner suggests:
In my view, if we are to solve this problem, we will need to look beyond people’s generation-relative preferences. Moreover, the prevalence of the intergenerational problem suggests that one set of motivations that we need to think hard about engaging is those connected to moral beliefs about our obligations to those only recently, or not yet, born. This leaves us with one final question. Can the abrupt paradigm assist us in this last task? Perhaps so: for one intriguing possibility is that abrupt change will help us to engage intergenerational motivations.
(Thanks to Simon Birnbaum for passing on Gardiner’s article.)
FAO reports that:
Twenty-two countries are … are in what is termed a protracted crisis, FAO said in its “State of Food Insecurity in the World 2010” hunger report, jointly published today with the World Food Programme (WFP).
Chronic hunger and food insecurity are the most common characteristics of a protracted crisis. On average, the proportion of people who are undernourished in countries facing these complex problems is almost three times as high as in other developing countries.
More than 166 million undernourished people live in countries in protracted crises, roughly 20 percent of the world’s undernourished people, or more than a third of the total if large countries like China and India are excluded from the calculation.
… Faced with so many obstacles, it is little wonder that protracted crises can become a self-perpetuating vicious cycle,” said the preface to the SOFI report, signed jointly by FAO Director General Jacques Diouf and World Food Programme Executive Director Josette Sheeran.
…For the first time, FAO and WFP offer a clear definition of a protracted crisis that will help improve aid interventions. Countries considered as being in a protracted crisis are those reporting a food crisis for eight years or more, receive more than 10 percent of foreign assistance as humanitarian relief, and be on the list of Low-Income Food-Deficit Countries.
Volcano eruption is certainly one, but which are other possible global surprises? In 1994, the Aspen Global Change Institute organized a two week workshop on global environmental surprise. The results from this workshop can be found in Stephen H. Schneider and colleagues 1998 article “Imaginable surprise in global change science” (Journal of Risk Research, 1(2)). By “imaginable surprise”, they mean
The event, process, or outcome departs from the expectations of the observing community or those affected by the event or process. Seen from this point of view, surprise abou t one or another aspect of climate change is an after-the-fact reaction to an observation or new scientific finding that, in some sense, lies outside our range of expectations.
In the list of 40+ types of surprises, you find not only volcano eruption, but also, just to mention a few:
Don’t say you weren’t warned….
Maybe it’s just part of my personal PCSD (Post Copenhagen Stress Disorder), but it seems like one of the most interesting topics emerging in frontiers of the earth system governance agenda, is that of building global institutions able to deal with not only incremental environmental change (e.g. biodiversity loss, land use change, climate change), but also crises.
Crises events (i.e. unexpected, high uncertainty, cascading dynamics, limited time to act) pose from an institutional point of view, quite different challenges than those normally addressed by the global environmental governance research community. These are related to the need for early warnings, multilevel networked responses, and improvisation. In addition, crises forces us to reconsider the way we look at communication technologies in global environmental governance [e.g. “Pandemic 2.0” in Environment here].
Oran Young’s brief talk from 2008 on adaptiveness and environmental crises, is not about environmental regimes in the conventional sense, but rather about the importance of role plays, simulations, and deliberations around unlikely, but high impact, scenarios:
The Center on International Cooperation (New York University) in addition, just recently launched a report entitled “Confronting the Long-term Crisis – Risk, Resilience and International Order”, that pretty much reiterates the point that debates around global governance are moving towards an agenda that focus not only single global environmental stresses, but also on multiple, interacting social-ecological ones.
* I owe the catchy title to my colleague Fredrik Moberg at Albaeco.
Nassim “Black Swan” Taleb writes on Edge about an unwillingness or consider and remember extreme events leads to financial disaster in The Fourth Quadrant: A map of the limits of statistics.
Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the “logic of science”; it is the instrument of risk-taking; it is the applied tools of epistemology; you can’t be a modern intellectual and not think probabilistically—but… let’s not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).
The current subprime crisis has been doing wonders for the reception of any ideas about probability-driven claims in science, particularly in social science, economics, and “econometrics” (quantitative economics). Clearly, with current International Monetary Fund estimates of the costs of the 2007-2008 subprime crisis, the banking system seems to have lost more on risk taking (from the failures of quantitative risk management) than every penny banks ever earned taking risks. But it was easy to see from the past that the pilot did not have the qualifications to fly the plane and was using the wrong navigation tools: The same happened in 1983 with money center banks losing cumulatively every penny ever made, and in 1991-1992 when the Savings and Loans industry became history.
It appears that financial institutions earn money on transactions (say fees on your mother-in-law’s checking account) and lose everything taking risks they don’t understand. I want this to stop, and stop now— the current patching by the banking establishment worldwide is akin to using the same doctor to cure the patient when the doctor has a track record of systematically killing them. And this is not limited to banking—I generalize to an entire class of random variables that do not have the structure we thing they have, in which we can be suckers.
And we are beyond suckers: not only, for socio-economic and other nonlinear, complicated variables, we are riding in a bus driven a blindfolded driver, but we refuse to acknowledge it in spite of the evidence, which to me is a pathological problem with academia. After 1998, when a “Nobel-crowned” collection of people (and the crème de la crème of the financial economics establishment) blew up Long Term Capital Management, a hedge fund, because the “scientific” methods they used misestimated the role of the rare event, such methodologies and such claims on understanding risks of rare events should have been discredited. Yet the Fed helped their bailout and exposure to rare events (and model error) patently increased exponentially (as we can see from banks’ swelling portfolios of derivatives that we do not understand).
Are we using models of uncertainty to produce certainties?
…So the good news is that we can identify where the danger zone is located, which I call “the fourth quadrant”, and show it on a map with more or less clear boundaries. A map is a useful thing because you know where you are safe and where your knowledge is questionable. So I drew for the Edge readers a tableau showing the boundaries where statistics works well and where it is questionable or unreliable. Now once you identify where the danger zone is, where your knowledge is no longer valid, you can easily make some policy rules: how to conduct yourself in that fourth quadrant; what to avoid.
Now it lets see where the traps are:
First Quadrant: Simple binary decisions, in Mediocristan: Statistics does wonders. These situations are, unfortunately, more common in academia, laboratories, and games than real life—what I call the “ludic fallacy”. In other words, these are the situations in casinos, games, dice, and we tend to study them because we are successful in modeling them.
Second Quadrant: Simple decisions, in Extremistan: some well known problem studied in the literature. Except of course that there are not many simple decisions in Extremistan.
Third Quadrant: Complex decisions in Mediocristan: Statistical methods work surprisingly well.
Fourth Quadrant: Complex decisions in Extremistan: Welcome to the Black Swan domain. Here is where your limits are. Do not base your decisions on statistically based claims. Or, alternatively, try to move your exposure type to make it third-quadrant style (“clipping tails”).
Below I’ve redrawn Taleb’s figure. His article provides a fuller picture.
Similarly, Scientific American reprints Benoit Mandelbrot’s 1999 How Fractals Can Explain What’s Wrong with Wall Street:
Individual investors and professional stock and currency traders know better than ever that prices quoted in any financial market often change with heart-stopping swiftness. Fortunes are made and lost in sudden bursts of activity when the market seems to speed up and the volatility soars. Last September, for instance, the stock for Alcatel, a French telecommunications equipment manufacturer, dropped about 40 percent one day and fell another 6 percent over the next few days. In a reversal, the stock shot up 10 percent on the fourth day.
The classical financial models used for most of this century predict that such precipitous events should never happen. A cornerstone of finance is modern portfolio theory, which tries to maximize returns for a given level of risk. The mathematics underlying portfolio theory handles extreme situations with benign neglect: it regards large market shifts as too unlikely to matter or as impossible to take into account. It is true that portfolio theory may account for what occurs 95 percent of the time in the market. But the picture it presents does not reflect reality, if one agrees that major events are part of the remaining 5 percent. An inescapable analogy is that of a sailor at sea. If the weather is moderate 95 percent of the time, can the mariner afford to ignore the possibility of a typhoon?
Jon Gertner writes in The Future Is Drying Up a New York Times Magazine about Water in the American West. The articles is discusses how increases in population and decreases in precipitation are reorganizing the US inland west. It includes some insightful comments from Roger Pulwarty, a climatologist at NOAA who looks at adaptive solutions to drought. He sounds a bit like Emory University ecological management scientist Lance Gunderson:
You don’t need to know all the numbers of the future exactly,” Pulwarty told me over lunch in a local Vietnamese restaurant. “You just need to know that we’re drying. And so the argument over whether it’s 15 percent drier or 20 percent drier? It’s irrelevant. Because in the long run, that decrease, accumulated over time, is going to dry out the system.” Pulwarty asked if I knew the projections for what it would take to refill Lake Powell, which is at about 50 percent of capacity. Twenty years of average flow on the Colorado River, he told me. “Good luck,” he said. “Even in normal conditions we don’t get 20 years of average flow. People are calling for more storage on the system, but if you can’t fill the reservoirs you have, I don’t know how more storage, or more dams, is going to help you. One has to ask if the normal strategies that we have are actually viable anymore.”
Pulwarty is convinced that the economic impacts could be profound. The worst outcome, he suggested, would be mass migrations out of the region, along with bitter interstate court battles over the dwindling water supplies. But well before that, if too much water is siphoned from agriculture, farm towns and ranch towns will wither. Meanwhile, Colorado’s largest industry, tourism, might collapse if river flows became a trickle during summertime. Already, warmer temperatures have brought on an outbreak of pine beetles that are destroying pine forests; Pulwarty wonders how many tourists will want to visit a state full of dead trees. “A crisis is an interesting thing,” he said. In his view, a crisis is a point in a story, a moment in a narrative, that presents an opportunity for characters to think their way through a problem. A catastrophe, on the other hand, is something different: it is one of several possible outcomes that follow from a crisis. “We’re at the point of crisis on the Colorado,” Pulwarty concluded. “And it’s at this point that we decide, O.K., which way are we going to go?”