Just a quick clarifying post, following the previous PhD wiffle, where I picked on the transition movement to come up with some modelling questions. I want to say this now so I don't keep on repeating myself in later posts: it's not my intention to try and disprove the relevance of what the transition movement is doing. Whatever the merits of any assumptions its actions are based on, I have nothing but the highest respect for people working to reclaim some direct control over their own economic destinies. I am acutely aware that one of the historic roles of quantitative modelling (whether implicitly or otherwise) has been as a tool to justify robbing people of agency. This is especially true in its most pervasive form, finance-ministry-condoned economic methods: incredibly consistent across the world, and something no-one has a great deal of choice in since the vast majority of political parties do little more than tinker at the edges.

That use of models is, unsurprisingly, not something I have any desire to contribute to - but I don't think that should mean rejecting quantitative methods as a tool for helping steer our direction of travel. Economic self-determination is a good thing - I see no reason why quant methods shouldn't support it. We should have a future where quant planning tools work with the grain of democratic decision making and public action. There are reasons why, theoretically, quant tools have tended to go against that grain; again, that's a topic for later.

It's not an easy problem to solve. Here's an instructive example I hope to study in a bit more depth, off the back of this paper (a colleague of mine is a co-author). It aims to probe the idea of `smart cities'. The concept has, it seems, gained a lot of traction in US planning circles; David Roberts has argued strongly in support of the idea and his articles via that link give a good overview.

But the `takeaway for practice' from the JAPA article is:

Urban form policies can have important impacts on local environmental quality, economy, crowding and social equity, but their influence on energy consumption and land use is very modest: compact development should not automatically be associated with the preferred spatial growth strategy.

That's quite a modest set of conclusions: `compact development' is not necessarily a carbon and energy cure-all. The fundamental reason the paper finds this is that it actually adds some economics of land use to the problem. I need to get a special symbol for "I'll come back to this"... but the crucial part of this story has been the reaction: it seems to have caused a pretty intense ruckus among those with a deep commitment to the smart growth / smart cities idea.

Which leads me to wonder about the problems involved in linking quant/economic modellers and decision-makers - not just policymakers, but the kind of people working at a local level in the transition movement. It's easy enough to envision some perfectly healthy relationship between the two, but the reality is (and has always been, actually) pretty dysfunctional.

One solid reason for that: it's much harder to roll a boulder up a hill when someone's following you up questioning your rolling method the whole time. Social action benefits from having an agreed set of assumptions to work with. Despite these thoughts on the transition movement I am still, when it comes down to it, quite unsure about some of the fundamental assumptions that drive it. But like that climate cartoon ("what if its a great hoax and we create a better world for nothing?") dense economic webs made up of a froth of small-scale activity stand entirely on their own merits. Cop out? Hmm.

Update: but I reserve the right to change my mind about quant models. There's a small but definite risk that, on further investigation, it might become obvious that the democratic downsides outweigh any actual insight they might supply, and we should thus break the fingers of all coders attempting to model society. Harsh but fair, and I'll offer my own fingers up for the hammer first.

Another P3 comment related to this link about recent permafrost stories (arstechnica; New Scientist).
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Update: MT corrects me. "I was pleased that the Ars and New Scientist articles did not flog the tundra-carbon-feedback-bomb panic, which does not have much support among scientists. I am a bit chastened that you still read it in there. // We are being quite stupid indeed. But this particular aspect is a concern that is widespread in the public but not among scientists. It’s not quite as baseless as the “Gulf Stream shutdown” one was a few years back. But both concerns were extremely overdrawn and basically inaccurate."
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This really drives home a sinking realisation. While pretty much all our political and research structures continue to develop around a 2 degree target, the reality is turning out to be very different. As a researcher, I see the various UK funding councils fitting into that ‘how do we fix the climate problem’ way of thinking. This is leaving us with no systematic research agenda to address what are looking to be fairly likely outcomes, including a global permafrost hand-grenade thrown into the climate system.

Our research institutions have foresight enough to see the change in currents ahead but they’re ignoring the massive waterfall and the drop beyond.

That’s a huge generalisation, I’m sure there are many working on these kind of what-ifs. My point is, those what-ifs need a much more strategic, broad attack. We are managing to push ourselves towards territory that, really, not that many people bothered to consider in depth because no-one thought we’d be this stupid. We are this stupid. So we have mainly only vague statements like “may threaten the very fabric of civilisation” etc.

For anyone who thinks our civilisation has some value worth fighting for, we’re going to have to do a lot better than that. If we are going to be this stupid, can we at least do it intelligently?

Another P3 comment and an unformed braindump. This is confusing stuff and I'm a long way from spotting a path through it.
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There's some digging to be done into the recent resurgence of DDT + GM related stories. I got myself tangled in the GM stuff (defending the tech in the face of what I and others considered a badly misinformed protest) but pull that thread and a whole lot of baggage comes with it. e.g. old Monbiot stories about marxists-turned neoliberals starting science lobby groups (also active during the recent Rothamsted protests) or the GM Watch stuff. Climate scientist Simon Lewis was wondering on twitter: "perhaps it's important to ask of scientific experiments: is this the science of the 1%. Or the 99%", suggesting that any attempt to separate science from the issue of control or money was not possible. (Ironically plenty of climate deniers would completely agree.)

Well, as long as it keeps on tricking me into writing shit down, I'll keep on unashamedly writing stupidly long comments no-one in their right mind would wade through and posting them here. Makes me feel like I'm keeping busy! That said, in a zero-sum world where I could be writing papers or blathering on blogs, I wonder which I should be doing...?

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We've got into discussions on P3 before, here and here, though not really coming to any conclusions. But you'll see we've picked up on a fair few things you've mentioned - one of my bugbears being the misuse of Friedman's 'F-twist' argument, claiming he says "unrealistic assumptions don't matter" (something I also repeated until, looking for ways to think about model-building, I actually read what Friedman said, which is subtly but vitally different to the caricature so often used to paint economists as naive Vulcan-like imbeciles.) A lot of that's come from my (still not quite finished!) thesis work; I've stuck the current version of the navel-gazing model chapter here. There's a lot of overlap, even many of the same quotes, with things your blog's discussing.

The most recent article of yours shares some of the same view of modelling in general. I'm not sure whether this eco-economics attack on modelling stems from quite the same source as MT's skepticism, would be interested to dig more into that. I think this starts getting close to the heart of this, which again comes down to what we're claiming models are *for* (which I waffle on about interterminably in that thesis chapter.) You quote the Daly/Solow argument (Daly: "If we want a bigger cake, the cook simply stirs faster in a bigger bowl and cooks the empty bowl in a bigger oven that somehow heats itself.") But you don't provide Solow's response; quoting meself quoting Solow:

"Solow's reply to this highlights a recurring argument used to defend the abstract nature of many economic models - critics are taking them too literally, and not considering how the models are used: 'We were trying to think about an interesting and important question: how much of a drag on future growth, or even on the sustainability of current production, might be exercised by the limited availability of natural resources and the inputs they provide? ... The role of theory is to explore what logic and simple assumptions can tell us about what data to look for and how to interpret them in connection with the question asked' (Solow 1997 p.267/8). Solow goes on to point out that the argument should be about how substitutable renewable and non-renewable resources are, given that the former are likely to be highly capital-intensive. (Ibid.) He appears to be saying that his critics have mistaken economists' models for their actual understanding of the world, rather than tools that aid that understanding."

Which is what I was arguing Krugman also says in the comment above, and what Friedman was saying way back in the 50s (though whether Friedman follows his own advice, I'm not qualified to say - I only really know his stuff from his 'essays on positive economics'). E.g.: when assuming s = 1/2gt^2, "under a wide range of circumstances, bodies that fall in the atmosphere behave *as if* they were falling in a vacuum. In the language so common in economics this would be rapidly translated into: the formula assumes a vacuum. Yet it clearly does no such thing."

And of course there are plenty of circumstances where it would be a completely inappropriate way to think about falling objects. But that doesn't make using it 'naive' or invalid, any more than using temperature and pressure measurements does (when we know that at atomic reality is more complex).

I haven't got to the bottom of this stuff to my own satisfaction at all. It would be great if we could carry on exploring them here at P3, but I wonder if that might require some kind of agenda!? I wouldn't mind starting with actually working up a common understanding of some economic models as they are. Stephen, it sounds like you have a solid economic background. I don't really; I've gone off and done this by myself while my supervisors looked on horrified, and found it immensely tricky to find economists to check my understanding with (perhaps my own networking failings, I shan't blame economists' closed-shop attitude!)

Some suggested things to discuss: understanding a basic general equilibrium model, how they've been used, how they're related (or not) to the actual policy workhorse DSGE models, what other models inform policy; whether economic training in these models is (as Krugman's own view seems to suggest) more a set of shared heuristics almost incidental to how economists are apprenticed in a policy episteme - so it's not 'about the truth of the models' so much about training and embedding policymakers. Which would mean we could attack the models til the cows come home and we'd be missing the point. You can actually see how that might function in a completely different context: Lansing's work on Balinese rice management, where a shared collective model allows autonomous ritual actions to both re-create the landscape and manage water to maximise crops/minimise pests across the Subaks. There's no 'correct' top-down model, there's a shared social technology tied into a specific landscape, kept alive in people's minds through ritual. Lansing calls it 'sociogenesis': "when Balinese society sees itself reflected in a humanised nature, a natural world transformed by the efforts of previous generations, it sees a pattern of interlocking cycles that mimic these cycles of nature" (priests and programmers p.133). Mainstream economics may partly work the same (esp. ritual!) but on quite a different scale (and of course with the open question of whether it's capable of ending in a cyclical self-maintenance or is instead a global virus; cf. Agent Smith).

It'd be good to explore a recent-history example of an economic model's impact: Krugman's core model again. Since 1991 it's gone from 'thought experiment to lure economists into thinking about geographical questions' (while also radically changing the profession's view of the central dynamics of international trade) to a World Bank report on geography coming straight from it, despite Krugman's own apparent caution on using it - and a continued suspicious lack of empirical support that shouldn't be a surprise given it was only ever meant as a toy model to make a point. (I've never quite understood what Krugman's own view of this is; initially caution and a notable silence as the Nobel prize arrived and some of the key ideas got absorbed by the body politic. But I'm sure he'd have some clear Views on it.)

And to ask the same question again: given all this, what role do we actually think models can / should play in both analysing and organising society? I have a book in front of me by Stan Openshaw, an ex-professor from my department, called "Using models in planning" (1978). A quote:

"Without any formal guidance many planners who use models have developed a view of modelling which is the most convenient to their purpose. When judged against academic standards, the results are often misleading, sometimes fraudulent, and occasionally criminal. However, many academic models and perspectives of modelling when assessed against planning realities are often irrelevant. Many of these problems result from widespread, fundamental misunderstandings as to how models are used and should be used in planning."

While he's writing about town planners, the same applies. We don't really understand how this is meant to work. It happens anyway, but without asking about this, we're stuck in this strange place where one side carry on using their models while others keep on going "ha! look at those stupid assumptions!" - as if by some miracle of alchemy, the models being criticsed will crumble like vampires at dawn. Kuhn's stuff makes clear it doesn't even quite work like that in the physical sciences: the relationship between discovering problems, errors, better models and the structure of a discipline is way more complex. If that discipline is then tangled into political power, there's a whole other bunch of stuff going on...