From Growth To Equilibrium – The work of Jay W. Forrester

The number of times you read a paper which seriously affects the way you view the world is depressingly low in the development business. Papers focus on the small-scale (does buying more text books improve test scores?) instead of the big picture (why are so many people starving to death?).

Among the papers which do seriously change your view of things, very few of them are accessibly written (see this blog post on Sen) and almost none contain laugh-out-loud moments or prose well-written enough to verge on poetry.

Eric D. Beinhocker‘s “The Origin of Wealth” is a well-known example, and I have now found one more. Jay W. Forrester‘s paper Counterintuitive Behavior of Social Systems left me reeling, dazzled by beautifully expressed ideas and charged with a new enthusiasm for research just as much as Beinhocker’s book did, but is something in the order of 50 times shorter. It contains all the ideas which are currently doing the rounds at the Center for Global Development‘s supposedly state-of-the-art thinking on development and complexity (see Owen Barder‘s fantastic lecture on this subject) and yet was written in 1971. (Note that all quotes will be from this article unless I say otherwise.)

The economists among us may have heard of Forrester as the originator of the Macroeconomics 101 favourite “Beer Game“, which was an entertaining MIT-originated way of demonstrating how well-intentioned attempts to improve a business, even those made by people with full knowledge of the business and complete understanding of the policy levers at their disposal, can lead to booms, busts and the highly unpredictable and chaotic behaviour seen in financial markets. Forrester says in this paper that these unexpected outcomes are the result of the human brain’s inability to follow through the logical conclusions of its understanding, or “mental model”, of the system it is trying to fix.

“Ordinarily [people’s] assumptions about structure and internal motivations are more nearly correct than are the assumptions about the implied behavior.”

A common example of this is the arguments around the impact of giving cash to people asking for money on the streets. We’re told not to do it, for reasons which sometimes appeal to complex cause-and-effect chains, but it seems counter-intuitive and against some kind of moral urge. According to Forrester this is because social systems

“…are inherently insensitive to most policy changes that people select in an effort to alter the behavior of the system. In fact, a social system tends to draw our attention to the very points at which an attempt to intervene will fail.”

Forrester uses an example from his time working in urban dynamics at MIT. He says that building low-cost housing in depressed areas can have counter-productive effects by (temporarily) lowering housing costs, attracting inward migration without creating any new jobs. More people and no new jobs only serves to depress the area further. This and other measures (including financial aid in the form of subsidies) are concluded to

“…lie between neutral and detrimental almost irrespective of the criteria used for judgement.”

Forrester maintains that social systems are complex, and that solutions are not to be found in the same places as symptoms (c.f. Ben Ramalingam‘s leading-edge thinking on malaria). It is unsustainable for any area of a country to be fundamentally more attractive (across all possible considerations of attractiveness), and if local development programmes succeed in:

…[making] some aspects of an area more attractive than its neighbor’s, population of that area rises until other components of attractiveness are driven down far enough to again establish an equilibrium.

Instead, he makes a plea for programmes which think of the wider system holistically, taking into account so-called “general equilibrium effects” which describe how the wider system reacts to changes in a certain area.

“Programs aimed at improving the city can succeed only if they result in eventually raising the average quality of life for the country as a whole.”

This advice clearly applies to development projects too, and it’s astonishing to think how little it is still being heeded in the vast majority of today’s development literature: Angus Deaton‘s hugely entertaining diatribe “Instruments, Randomization and Learning About Development” makes similar complaints, and was written some forty years after Forrester’s.

Another piece of advice which could have been written yesterday (c.f. seemingly every British government policy since Attlee) is that:

there is a fundamental conflict between the short-term and long-term consequences of a policy change… [We should be] cautious about rushing into programs on the basis of short-term humanitarian impulses. The eventual result can be anti-humanitarian.

He goes on to extol the virtues of mathematical modelling over “contemplation, discussion, argument, and guesswork” and presents an enormous, Heath Robinson-esque model of the world which he uses to predict global catastrophe from a variety of all-to-contemporary concerns including food production limitations, a pollution crisis and natural resource limitations. Let me just restate: this paper was written in 1971.

A Heath Robinson-inspired model of the world (Forrester, 1971)

He makes an ahead-of-his-time gloomy assessment of the outlook for international development, that there may be

“…no realistic hope for the present underdeveloped countries reaching the standard of living demonstrated by the present industrialized nations.”

Forrester then goes on to present possible ways of avoiding catastrophic population collapse cautioning that transitioning from the contemporary path of unsustainable growth to one of sustainable equilibrium will involve painful readjustments and unpopular policies (sound familiar? See this entertaining clip of Paul Krugman talking about fiscal consolidation during a recession, or any one of a million of his brilliant blog posts on the subject.) This stuff reminds me of the hugely impressive Diane Coyle, and her work on The Economics of Enough.

The paper ends with a little bit of more-optimistic poetry:

I suggest that the next frontier for human endeavour is to pioneer a better understanding of the nature of our social systems. The means are visible. The task will be no easier than the development of science and technology. For the next 30 years we can expect rapid advance in understanding the complex dynamics of our social systems. To do so will require research, the development of teaching methods and materials, and the creatino of appropriate educational programs. The research results of today will in one or two decades find their way into the secondary schools just as concepts of basic physics moved from research to general education over the past three decades.

I wonder if, over forty years on and given that almost no one is working on development as a complex system, Jay W. Forrester is disappointed that this is the one area where his predictive powers seemed to fail him so spectacularly.

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Enough to reduce global poverty four times over

Today counts as an exciting day in the life of a researcher whose reading list consists more of Twitter and blogs than it does of JDE papers. (Should I be admitting to this in public? Something about the narrow micro-focus and lack of interest in external validity of most published works in the JDE and the like make me less worried about this than perhaps I should be. (Or am I reading the wrong journals?))

Following a piece I heard on the Today programme on BBC Radio 4 about wealth inequality, two of my favourite bloggers, Duncan Green at Oxfam and the mighty Owen Barder at the Centre for Global Development had a minor public disagreement in the comments section of a blog post from Green about the same story.

The story, originated by Oxfam, is that the additional wealth earned by the world’s richest hundred in 2012 could have ended global poverty four times over, and it was in this exact form which the story was reported on the BBC. Green’s blog post went into more detail about how the figures were arrived at (something which I think characterises his lucid and reasoned blogging style) but Barder questioned the accuracy of the “end global poverty” part of the Oxfam status.

The definition of ending global poverty was giving people enough money to take them over the $1.25-a-day threshold, the World Bank’s definition of extreme poverty. Barder pointed out the difference between this narrow definition and that which many people will have had in mind when they heard the phrase “ending global poverty”. (I’m paraphrasing/expanding here, but I think the sentiment is correct. The actual tweet is here.) Green then admitted that the ending of global poverty would only happen in “the narrow sense of extreme income poverty” to which Barder hilariously countered that Green had written an entire book attempting to get away from such narrow definitions of poverty (which comes with a recommendation byline from Amartya Sen himself).

The argument for me seems to exemplify the growing distinction between the world of blogging and the world of let’s call it “traditional” media: blogging at its best is all about honesty and straightforwardness; something I admire in both Green’s and Barder’s blogs. But the “traditional” media need simple one-phrase headlines which will capture the attention of the driving, snoozing, train-riding or otherwise partially-engaged listener/reader.

I think there is room for both, and I can completely see the benefit of simple headline stats like the world’s richest hundred one from Oxfam. (In fact, I think that stats like these should have some kind of permanent home: a kind of shockingfactsaboutinequality.org)

But the world also needs the Barders, Harfords and Goldacres to keep the lid on the sometimes overzealous preachings of those at the interface between statistics and the media.

The spatial distribution of human development

Let me get a quick admission out of the way, before I launch into this review of the freshly-published World Development article Using Census Data to Explore the Spatial Distribution of Human Development by Iñaki Permanyer: I don’t know much about human development indices. I know what a Gini coefficient is (in brief, a number which is close to unity if a few people have all the money, and close to zero if the money’s more-or-less evenly spread) but I haven’t read much from the long bibliography of this paper about the ins and outs of various ways of measuring human development. So, there’s a possiblity that I’m going to be over-enthusiastic about this approach compared to many other papers which I simply haven’t read.

But I must say, I’m hugely excited by the methods proposed by Permanyer in this paper.

In summary, he discusses a method of using very simple questions in the Mexican census to proxy for such unknowables as health, education and standard of living. He goes on to show that these proxies perform well in comparison to other, more difficult to obtain, metrics and that they allow a comparison between municipalities in human development terms.

The really nice thing about his method is that it doesn’t at any point rely on self-reported income or health; metrics which are famously inaccurately reported.

Instead he constructs an asset index to proxy for material welfare and a simple child mortality stat to proxy for health. These are incredibly simple to gather, and are not subject to misreporting.

A whole page of the paper is dedicated to the justification of using an asset index instead of income, included the hand-wringing worry that

…asset indices have been criticized because they might not correctly capture differences between urban and rural areas. Since many assets are cheaper, more easily available and more desirable in urban areas, urban households might appear to be wealthier than their rural counterparts.

This seems like a strange concern to me, since the whole point of using an asset index is to get away from traditional money-based definitions of wealth. As Amartya Sen (who seems oddly under-cited in this paper) would doubtless argue: if the assets in question add to the capabilities of the respondent, and the respondent happens to live in an area where the asset is cheaply available, then surely the respondent is indeed wealthier. This strong argument seems like an obvious omission to me.

The paper goes on to report the results of calculating these new human development indices using census data from 1990, 2000 and 2010 (data which the author needed “a special permit” to access) and the results are truly gripping. He shows a couple of fantastic choropleth maps (something which I’ve never seen in an economics paper!) and is able to calculate, using the fabulously titled kernel estimation, the change in distribution of these indices throught Mexico across each of the three census periods. This is where the real magic of the paper lies: the distribution graphs are wonderfully informative (they summarise tens of millions of data points into 6 curves!) and tell a powerful story of the success, and origins of, Mexico’s growth programmes over the last 20 years.

Finally, let me add that the paper is lucidly and well written (despite some English oddities which could have easily been ironed out at copy-editing: Permanyer insists on continually using the clunky construction that a method “…allows to…” do something cool) and that there is a nice example of disarming honesty.

Everyone in research, to some extent, bases their methodological decisions on what data are available but Permanyer makes this explicit:

The choice of municipality as unit of analysis has been basically determined by data constraints.

Great stuff, and a cracking good read the paper is too.

Knowing What We Can

A recent blog post of mine got all lathered up about the work of Toby Ord‘s charity-bothering organisation Giving What We Can. (Note: from the pictures on their website it seems that there are other people involved, but calling it “Toby Ord’s” is lazy journalese for the less wieldy “charity founded by Oxford researcher Toby Ord etc. etc.” Who wants accuracy when you can have brevity, eh?)

The organisation says it “provides information about the cost-effectiveness of different charities”, something which the people at the International Aid Transparency Initiative have been talking about for a few years now. (Note that if I’m quoting, it’ll be from givingwhatwecan.org unless I mention otherwise.)

Given the famous paucity of data available from NGOs about what they spend their money on, this is a pretty exciting claim. So how does it work?

Well, the first thing to say is that the only charities that are rated are those that “have a relatively narrow focus”. This makes perfect sense of course, since rating the biggies like Oxfam and MSF would involve rating hugely varied and various projects. That said, it serves to slightly water down Tim Wigmore‘s assertion in this week’s New Statesman that Ord’s research “shows there is a clear winner: charities that focus on single issues.” (Sorry Tim, I’m not intending to turn this post into some kind of hatchet job. It’s thanks to your article that I’ve heard of Toby Ord at all! But the point is probably nevertheless worth making.)

The next thing to clarify is that Giving What We Can (GWWC) are so far focused on health-related interventions, using cost-effectiveness data from the World Heath Organisation (WHO) and figures on the global burden of disease from the Disease Control Priorities Project (DCP2). This is also an eminently sensible first step since GWWC base their charity rankings on something called disability-adjusted life years (DALY), a WHO metric which accounts for both length of life and, crucially, quality of life. (By the way, the weights given to each disability in terms of its negative impact on quality of life make fascinating reading in themselves.)

This helps to explain why GWWC’s top-rated charities are all health related, namely: the Against Malaria Foundation, the Schistosomiasis Control Initiative and Deworm the World. These JPAL-style health interventions have been shown to be hugely effective in boosting test scores and school attendance as well as in having the obvious impact on quality of life which not having a disease affords you. But it’s worth making the point that these charities are the most effective of the single-issue health intervention charities, not the most effective of all charities overall. Given the huge importance of this knowledge in itself, I don’t see that the message would be robbed of relevance by making this explicitly clear.

I think projects like this are what make the open data movement in aid so important and so exciting. The idea behind the movement is that simply by making information available, passionate and talented researchers such as Ord and his team will turn the data into knowledge which can be used by the public at large (or even policy makers) to inform their donation decisions. I think that what GWWC have done with the statistics is remarkable.

But it’s also important that the limitations of What We Can Know are made clear when we decide What We Can Give.

Sen is everywhere

I’m sure I’m not the only one to have had a hard time reading Amartya Sen’s Development as Freedom^* on the tube or in a cafe. It’s serious reading and requires a suitably contemplative atmosphere to avoid the dreaded “I’ve read this sentence three times now, and I still haven’t taken anything in” effect. It’s very precisely written, with little wasted (although to be fair, a helpful amount of repetition of the main ideas) and feels a little like reading maths. (Or, perhaps, like reading philosophy which, apart from the obvious, I’ve never seriously attempted.)

Anyway, it cheered me somewhat to see an article in the New Statesman (11-17th January 2013) by Tim Wigmore, apparently nowhere to be found online, entitled “Give a little, but give it well”. The article is a plea for evidence-based targeted of money to charities and describes the work of givingwhatwecan.org who claim to be able to rank charities based on their ability to “provide the greatest return in terms of quality-adjusted life years” for each quid donated.

Two things strike me as interesting about this:

1. Ranking charities in this way seems to me to be a direct application of Sen’s plea for a more rounded “capability approach” to assessing development: rather than focusing on how much incomes are increased by a given development intervention, he proposes we look instead at which things the people involved are able to do which they couldn’t do before. (Only things which the people themselves “have reason to value” are to be included in the list. These are things which Sen refers to as “substantive freedoms”.) It’s encouraging to see practical applications of Sen’s philosophy making it into a popular weekly magazine. It also makes me think it was worth the effort to read the book in the first place!
2. Given the famous difficulty in knowing what NGOs are doing with their donation money, it seems incredible that one organisation can not only find this stuff out, but find it out in sufficient detail to be able to compare across organisations in terms of an effectiveness metric. Amazing.

So, with this in mind, I’m off to find out how “Giving What We Can” are able to do what Wigmore says They Can, and also off to continue to enjoy/battle through Sen’s heavy-hitting classic, the effects of which are clearly still being felt throughout the development research community.

^* Sen, Amartya 1999 – Development as Freedom, Anchor Books