How do people respond to disasters?

You can sit and wait for the Government to send help, of course, which in any case can provide some opportunities for political demagoguery. Or you can do what you can to help yourself. And you don't need to be a survivalist to choose the latter course.

On this 5th anniversary of Hurricane Katrina's devastation of New Orleans and the Gulf Coast, check out the Gulf Coast Recovery Project at George Mason University's Mercatus Center, started in the immediate aftermath of the disaster:

In 2005, Mercatus launched a five-year project to follow the long-term redevelopment of the Gulf Coast after Hurricane Katrina. By combining verbal interviews with people rebuilding the Gulf Coast and quantitative and qualitative data, the Gulf Coast Recovery Project seeks to better understand the array of complex issues facing communities recovering from disaster and the roles that the public, commercial, and non-profit sectors play in rebuilding communities affected by large scale catastrophes.

There is now a great wealth of information on the site -- working papers, talks, videos, forums, media files, etc. -- examining the question in the title of this post, and finding some interesting answers.

A cultural Uncertainty Principle

This is a kind of extension of that "attitude of epistemic humility" discussed in an earlier post. That stemmed from an article by Jim Manzi speaking of the difficulty in assessing the effectiveness of economic policies, because of the impossibility of assessing counterfactuals -- i.e., of knowing what would have happened without the policy, or if a different policy had been in place. That's a fairly narrow limitation, however, and I've already suggested ways in which such uncertainty could be reduced at least (e.g., examining different policy approaches to the same problem in different jurisdictions, etc.). But Manzi's piece itself refers back to his own earlier and more general article in City Journal on "What Social Science Does -- and Doesn't -- Know" (subtitled "Our scientific ignorance of the human condition remains profound.").

In that he brings up another kind of complication that arises in medicine and then in the social sciences, which he calls "causal density":

... as experiments began to move from fields like classical physics to fields like therapeutic biology, the number and complexity of potential causes of the outcome of interest—what I term 'causal density'—rose substantially. It became difficult even to identify, never mind actually hold constant, all these causes.

Which is a good point, though it's certainly been noted and complained about previously. And in thus merging social science with medicine, it obscures a much more problematic source of trouble. Which is this: behind every hypothesis that's tested in a scientific experiment there lies a theory of some sort, though not always an explicit or well-formulated one, nor even necessarily a conscious one. In the latter case, of course, we're talking about unconscious assumptions that can affect the whole design and outcome of the experiment or study. In the physical sciences, such assumptions are usually the result of insufficient care or analysis (leaving Kuhn aside for now), and there is a strong culture dedicating to exposing just such faults. But in the social sciences, these kinds of assumptions are very commonly interlaced with social and political values, and attempting to expose them can involve much more complex and deeply rooted political issues and conflicts, rather than simply scientific or rational ones.

So this is the first source of inherent uncertainty in this area: in touching upon our social position in the world, social science cannot avoid the political issues involved in its research -- it is inherently politicized. And unfortunately, as we all know, it's politicized largely in one direction -- toward the liberal-left (see, e.g., "The Social and Political Views of American Professors" [PDF], by Gross and Simmons, 2007, as just one among many indicators). All too often, this results in "studies" that show mainly what the studier wants them to show, though of course they usually go through the motions of a "balanced" enquiry. Such studies are what Richard Feynman referred to as "cargo cult science": "they follow all the apparent precepts and forms of scientific investigation, but they're missing something essential", which he calls "scientific integrity", but which is often manifested in a serious commitment to finding holes, flaws, weak points, over-statements, falsifications, in both one's own and others' work. But that's precisely what's so difficult when dealing with issues that touch upon one's deepest convictions.

And there's another, even deeper, source of social science uncertainty. Knowledge or understanding is an important -- in many ways, central -- aspect of what we are, and it has a decisive effect on how we behave.  But, even allowing for the inherent ideological bias mentioned above, social science itself is knowledge, and hence that knowledge itself affects -- i.e., changes -- the behavior of its object of study. There is therefore an Uncertainty Principle at work in attempts to make a science of human behavior -- not as precise as Heisenberg's, certainly, but analogous in the way in which the observed is unavoidably affected by the observer. It's an effect that has shown up repeatedly in economics, where predicted behavior patterns are internalized and taken into account, with the resultant behavior only explicable in hindsight. It's the "unintended consequences" that perpetually operate to limit the designs of would-be social engineers.

Social science, therefore, faces multiple sources of uncertainty that physical sciences do not -- in order of increasing severity or intractability, they are

• the difficulty in disproving counterfactuals;
• what Manzi refers to as the "causal density" of social phenomena;
• the inherent politicization of social questions;
• and the Cultural Uncertainty Principle: the inescapable and unpredictable effect that social knowledge has on social behavior.

All of these need to be borne in mind whenever encountering the "studies show" line so often used to justify the technocratic manipulation of social outcomes.

"an attitude of epistemic humility"

That's a quote from the end of a Jim Manzi article in TNR: "Confusion Reigns at TNR on the Stimulus ... For Good Reason". The confusion he's talking about has to do not just with differing opinions, Keynesian and otherwise, over the effectiveness of the "stimulus" itself, but also with a spreading recognition that there is no good way even to assess its effectiveness -- because however good or bad the results of a policy, you can always argue that they would have been better or worse if the policy hadn't been in place. As he says (quoting himslef in an earlier article), "we have no reliable way to measure counterfactuals".

Now, this may be a little too humble -- if a policy is implemented on the basis of some projection of its results, and that projection is then shown to be wrong, it's at least going to cast some doubt on the policy and the theory underlying its projection, which is what's happening now with the Stimulus and its Keynesian defenders (Krugman, e.g.). And often there are other ways of assessing than through counterfactual reruns of history -- such as by comparing different approaches to the same problem in different jurisdictions, as Josef Joffe, a colleague of Manzi's, does in "The International Stimulus Sweepstakes: Who Wins?". (See also this post by Megan McArdle, on "Hoovernomics".) But in general this lesson that we have a difficult time, even after a policy has been put in place and operating, much less before, in knowing whether and to what degree it was effective, should restrain the urge to make very large bets, using other people's money and lives, on theoretical/ideological premises.

Suppose, now, that we were to change focus, and apply a little of that "epistemic humility" to the climate debate. We'd see a greater recognition of the inherent uncertainties in long-range climate modeling in the first place, and much greater attention paid to the huge uncertainties inherent in efforts to model real economic costs and benefits inherent in any policy approach toward the issue, in the second place. It's the latter, of course, that should give pause to anyone not a zealot. When the situation is one in which any action, including no action, carries risks that are difficult or impossible to calculate, it's generally not a good time to make a large leap of faith/ideology. Instead, Manzi's proposed guidelines for policy in the face of this kind of uncertainty seem like a much more rational approach, to climate change as well as to economic crises:

... “boldness” in the face of ignorance should not be seen in heroic terms. It is a desperate move taken only when other options are exhausted, and with our eyes open to the fact that we are taking a wild risk.... We are walking into a casino and putting $800 billion dollars down on a single bet in a game where we don’t even know the rules. In general, in the face of this kind of uncertainty, we ought to seek policy interventions that are as narrowly targeted as is consistent with addressing the problem; tested prior to implementation to whatever extent possible; hedged on multiple dimensions; and designed to be as reversible as is practicable.

Carbon taxes as a means of forcing down global emissions to some early industrial level are an example of a policy too grandiose, too uncertain, and too premature to meet these criteria.

Liberty, the knowledge problem, and social evolution

We've seen that Jim Manzi's distinction between liberty-as-goal and liberty-as-means libertarianisms runs into some immediate problems and false paradoxes. Better to contrast dogmatic libertarianism with a pragmatic version, that aims simply to increase liberty in an incremental, experimental manner. But there are deeper issues involved in the notion of liberty, both as goal and means, that Manzi also raises, though again in a somewhat tangled fashion.

The first of these is the famous "knowledge problem" (see, e.g., Hayek's "The Use of Knowledge in Society"), which can take various forms, but can be expressed as the idea that the dispersion of decision-making power amongst the individuals affected by decisions takes maximum advantage of their knowledge of their own circumstances. In this sense, we might say that liberty -- that is, the dispersion of decision-making power -- is a means to the end of maximizing individual well-being, in whatever way individuals define it. But this, by its emphasis on the individual's definition of her own well-being, and by its very generality, comes quite close at least to being equivalent to simply making liberty a goal -- we might say that it helps explain why liberty is a goal.

Manzi may be alluding to something like this in his assertion that "We need liberty ... because we are so ignorant of what works in practical, material terms". But, in bypassing the individual emphasis, it misses a critical aspect of the issue, and leads him into the false paradox noted earlier, where liberty, and the ignorance it addresses, is apparently satisfied simply by dividing society into smaller units, each of which is "free" to be relatively repressive or anarchic.

But perhaps Manzi has in mind another kind of ignorance than the Hayekian notion of the dispersion of knowledge -- perhaps he's simply referring to the limits of human knowledge in general. Here, for example, are the sentences that preceded the quote above:

Liberty-as-means libertarianism sees the world in an evolutionary framework: societies evolve rules, norms, laws and so forth in order to adapt and survive in a complex and changing external environment. At a high level of abstraction, internal freedoms are necessary so that the society can learn (which requires trial-and-error learning because the external reality is believed to be too complex to be fully comprehended by any existing theory) and adapt (which is important because the external reality is changing).

 And here (finally) is a clear and important realization. Let's try to make its components even more explicit:

• First, social/cultural evolution is not something brought about by design -- by social engineers, policy-makers, or bureaucrats -- but rather by the same sort of random, trial-and-error processes that we see in the natural world; it's Darwinian, in other words, as opposed to Lamarckian. This isn't because human knowledge is futile but simply because it has limits, outside of which nature always waits and exerts her influence -- it's just that influence that appears as evolution, as distinct from, say, "improvement", "reform", "institutional design", "revolution", etc.
• But, second, such evolution isn't something distinct or apart from human agency, but rather consists of human decisions and actions, and of course of the consequences thereof. Manzi is right to point out, therefore, that the dispersal of decision-making power in the face of this sort of unavoidable ignorance confers a distinct evolutionary advantage on a society, in terms of the greater flexibility and adaptability it allows. There are, as he also points out, limits to this dispersal, or issues on which coercion is still an evolutionary advantage (e.g., obviously, laws against murder or theft, or, arguably, laws against prostitution), but everywhere the evolutionary logic is to disperse this power as far as possible, thereby extending the freedom of the individual agent.