Tag Archives: public policies

Thinking in networks: what it means for policy makers

Elegant, influential theories have a way to rewire your brain. In my formative years, it was not uncommon to joke that Marxist intellectuals could and would explain absolutely anything in terms of Marxist dialectics. For all our joking, exactly the same thing happened to me, as I dug deep into neoclassical economic theory. I did have access to non-neoclassical theories, but in the end it is the math that makes the difference. Mathematics gives you a grip on the model: by manipulating it, you can stretch it, adapt it, critique it, own it in a way that you can’t really any other way. In the end, the mathematical tools you use to think about the world become a default way to parse empirical data: when your only tool is a hammer, you see every problem as a nail and all that.

The hammer of neoclassical economics is functions. Not just any old function: convex, continuous, differentiable ones – designer functions with smooth hypersurfaces. If everything is a function of this kind, everything (say, your country’s economy) must have a maximum, because (bounded) continuous, convex and differentiable functions have exactly one max. This means there is a perfect (“optimal”) state of the world. You find it by calculus. You can then hack your way around the system with taxes, subsidies and interest rates until you push the economy to that maximum. If you are a consumer, or a worker, you also will be looking at a function, representing your well-being. Again, you can find its max, fine-tuning savings and consumptions, work and leisure into your personal sweet spot. There’s no such thing as unemployed: hey, the function is not discrete! What you are seeing is people that choose to allocate zero hours to work, given the existing wage rate (I exaggerate, but not much).

I spent the past five years learning how to use a new mathematical tool: networks. Going deep into the intuition of the math (as opposed to memorizing the equations) means, in the long run, a rewiring of your brain. What used to look like a nail suddenly makes much more sense as a screw. A good thing, since you are now the proud owner of a screwdriver! What I am seeing now as I consider public policies is this: I think of them as signals that the policy maker sends out. The interesting question is what carries the signal.

Traditional policy signals are broadcast: every agent in the economy receives the same message. Price signals (hence taxes and subsidies, too) are broadcast. So, in general, is regulation. Broadcast makes a lot of sense in an undifferentiated mean: if you want to reach a large number of recipients and they are all disconnected from each other, it’s a good technique. Just push that signal out in all directions, as loud as you can.

Once you really take networks on board, though, you start seeing them everywhere. And when you have all sorts of networks that could carry the signal for you, broadcast seems a blunt way to do things. Consider AIDS prevention policies. Broadcast policy sees that, as a category young people are more likely than old-timers to engage in unsafe sex, so it puts posters up in high schools. Since you can’t really be too graphic about it for political reasons, such posters tend to be quite bland, and immediately drowned by far stronger broadcasting signals that glorify sexual prowess and availability, those of commercial markets. Even if your average teen does become more careful, the epidemics still spreads through the very promiscuous few, who are unlikely to be impressed by a bland poster. All in all, near-zero impact is a good guess.

On the other hand, research has shown that networks of sexual partnerships are scale-free: a small number of individuals (not categories) have a very large number of sexual partners. These people are the main vector for the virus to spread. So here’s the networked version of AIDS prevention policy: go talk to the hubs. Dispatch researchers to identify them (it does not matter where you start, with scale-free networks it will take a small number of hops before you get to one); have one-on-one conversations with them. Spend time with them, they are important. Show them the data. Hire them, even. Should be cheap: it’s only a handful of people, who can have a disproportionate amount of impact on the epidemics by switching behavior. See the difference in approach?

In my talk at Policy Making 2.0 last week I tried to explore what it means, for policy makers, to think in terms of networks. I proposed that the gains from doing so are:

impact: more bang for your taxpayer buck.
reduced iatrogenics: policy becomes more surgical, so it causes less unintended damage.
robustness to “too big to know”. Very simple network models exhibit sophisticated behavior. You can model several real-world phenomena without losing your grip on the intuition of the model, and therefore make more accountable decision.
compassion. Networks owe their uncanny efficiency in carrying signals to large inequalities in the connectedness of nodes. Further, it is easy to build very simple models that produce inequalities even with identical nodes. This, at least for me, gets rid of the “underserving poor” rhetoric and fosters simpathy towards the smart and hard-working people out there that found themselves on the wrong side of system dynamics.
measurability. Social interactions that happen online are now cheap to keep records of; you can use those record to build networks of interactions run quantitative analysis on them.

If you want to know more, you might find my (annotated) slides interesting. I am indebted, as ever, to the INSITE project and to all participants in Masters of Networks.

Do no harm: when well-meaning public policies hurt society

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Just as I prepare for Policy Making 2.0, I wonder if we are not missing something important there. I am as fond of technology, science-based modeling and data-powered approaches as the next guy. And yet, the technology, the modeling and the data crunching are just the glazing of the policy making cake. The dough beneath it, orienting the deployment of our technological wizardry, is the policy maker’s world view – and that is in bad need of an overhaul.

Let me explain. I find that the vast majority of policy makers – regardless of their political preferences – subscribe to a linear model of policy. An issue is detected; it works its way into the political discourse; an approach is found to tackle it and validated by democratic vote; leaders make it into regulation; such regulation is then enacted by the executive branch, to the desired effect. The linear model may sound reasonable end even “evidence based” if the process leading to crafting the response includes data processing. But it holds only if society is like a machine: relatively simple and tractable, with no second-order effects. If you believe this to be an acceptable approximation of reality, you’ll like the linear model just fine. Traditional economics does: I have sat in classes where optimal policy is computed by maximizing a social welfare function, itself the result of aggregating each individual’s utility function. If your economy is not at the maximum, you should (and you can, in principle) push it there by manipulating the price system (through taxes and subsidies), the level of economic activity (through tweaking taxes and spending) and financial constraints on economic agents (through interest rate fixing, quantitative easing, reserve requirements etc.) and regulation (like standard setting).

If you, like me, believe you are living in a highly nonlinear world, resembling an ecosystem much more than a machine, and better understood by a complex systems approach, then the linear model will not work for you. Neither will its tools – taxes, subsidies, spending, monetary policy, regulation – be reliable.

It’s not a just a matter of not working. I am becoming convinced that deploying these tools can be downright harmful. In trying to correct for a perceived distortion, the state applies some pressure to try to offset the distortion. But, all too often, the economy reorganizes as individuals try to take advantage of the state’s intervention. An example with regulation: to contrast the proliferation of short-term employment, a government might make it more expensive to hire on a temporary basis. And companies might respond more or less forcing would-be employees to start one-man businesses, so as to transform employees into suppliers. Result: even more insecurity for the people in question. Another example, this one with spending: a government decides to encourage R&D spending by funding joint research projects between companies and universities. Problem is, when companies see a business opportunity, they will typically not wait for public funding, but just go ahead with the project. Later, they might apply for funding to pay what they have already done – shifting the burden of paying for the R&D to the taxpayer while not generating any additional new product. Final result: much application forms writing, many projects (with high overhead) funded, but very few new products.

Both these things – give or take some important technicalities – have happened in Italy. The distortion of a local economy by massive public spending is visible to the naked eye: you talk to smart, entrepreneurial young people in Italy’s Mezzogiorno, and chances are they will be aware of the main programmes funded by the European Social Fund, the European Regional Development Fund and their national counterparts. A discouraging amount of their time goes into second-guessing funding agencies and writing applications with all the right buzzwords. And why not? It’s the biggest game in town. Italy’s Strategic National Framework allocates 125 billion euro to economic development over the 2007-2013 period (source, p. 236). That’s a lot of money. To give you a benchmark, World Bank lending commitments worldwide for the same period amount to less than 200 billion euro (source – the page, as I can’t seem to reference the graph directly).

Of these, 101 are concentrated in four regions in the Mezzogiorno (rightly) perceived as lagging behind. Regions are the main spending agencies in Italy: this allocation of resources means that the four regions in question need to juggle the administrative workload of funding, in an accountable way, an average of 3.5 billion euro per year on regional development projects alone – whereas the remaining 15 regions “only” allocate an average of 200+ million per year to the same end. Since money This results in chronic underspending by the least developed regions, who struggle to manage this flood of money.

This accounts for the distortion in incentives I mentioned above. While a great majority of public spending ends up going through traditional channels – incumbents and old boys networks, like everywhere – many of the best and brightest people in Italy’s Mezzogiorno end up spending a lot of time thinking on how to get a piece of the action. Recently, my friend Tiago Dias Miranda spent some time in Basilicata and reported:

[…] one of the first things that struck me was the fact everyone kept on talking about bandi, which at first I thought it had to do with music bands. Little did I know bandi means “competitions” [public sector tenders and calls for proposals]. […] unless there is an elephant in the room that I haven’t seen— this territory is highly subsidised, just like developing country receiving donations from the wealthy families.

Most people, within government and without, are aware of this effect of spending, but see it as a necessary evil. “We have to do something for lagging regions – they say – This way of doing things may be inefficient, but it does move things in the right direction, bringing about more work and opportunities.” But here’s the catch: this argument only holds if you accept the linear model. If the economy is complex enough, self-organizing effects begin to show. People on the ground try different things (in Basilicata many people have been exploring tourism services, for example), tinkering with their lives and economic activities. Some selection mechanism functionally similar to natural selection for evolution rewards the successful strategies and eradicates the unsuccessful ones. The former get imitated by more and more people, while the latter go extinct. This gives the system a measure of self-healing, of bouncing back – unless, that is, an injection of public spending keeps the attention of innovators on goals set by the funding agencies and off the tinkering-then-selecting activity.

Tiago’s observation that “everyone is talking about tenders” in Basilicata implies that, in a different situation, the same people would be talking about something else. Maybe they would start companies; maybe they would migrate; maybe they would squat abandoned buildings. But they are not doing those things, and this is actively harming the local economy and society, pushing it into a spiral of dependency. In medicine, this would be called iatrogenics; physician’s actions that harm the patient, despite the best intentions.

Per se, these observations are not new – Dambisa Moyo and others have eloquently argued that too much public spending – no matter how well meaning – can hurt a local economy. But they are counterintuitive, and they never made it into the mainstream. In Italy, certainly, the political discourse is all about how much money you can amass behind which goal; so, the point bears repeating.

More interestingly, I am thinking hard about ways to do two things to operationalize these ideas:

diagnose when it is that local economies are complex enough to find an adaptive path towards improvements. This is harder than it sounds, because you have to choose an appropriate level for the analysis, and whichever level you choose you will likely have winners and losers within that level. For example, Italy is definitely big and complex enough to do interesting stuff, but historically it has tended to concentrate the action in the north, with southern regions lagging behind. If you look at the level of a small region, you are almost sure to find, again, areas that are quite dynamic and areas that are not.
suggest tools that lend themselves well to a “do no harm” approach, that assumes you are doing public policy on a complex adaptive system, not on inert matter or on a simple machine.

These will be the subject of forthcoming posts.

Blog like it’s 2004

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For a few years now I have been participating in various social networks. But I never abandoned blogs, neither as a blogger nor as a reader, and I have no intention to do so. After seven hundred posts and two thousand comments, I am very grateful to this blog: it put me in touch with people and ideas that have become important in my development (on top of everything else, I owe it my present job). Blogging helps me organize my thinking, and not to get lost while moving along a trajectory which is not all that linear.

I am also grateful to other people’s blogs. Over the years, my preferred reads have changed almost completely, as both my interests and those of my once-favorite bloggers shifted; but I continue to enjoy the relationship I maintain with the bloggers I do follow, certainly intellectual but strangely intimate. Long-haul, sustained engagement with the thinking of a bunch of smart individuals, seems to help me develop my own. So, I am dedicating this post to the second generation of my blogroll, the blogs I am reading and commenting now, in the spirit of 2004 and of the brief golden age of blogging.

As far as Internet-enabled public policies and open government I am still reading David Osimo. David is based in Brussels, so he has a usefully European perspective, though in the past year he has been writing less than previously. A few months ago Beth Noveck came back online, after a long pause from blogging due to her responsibilities with Open Government at the White House. I hope she keeps it going, it is a really important contribution.

Thanks to Dave Kusek and Francesco D’Amato I can keep the economics of mucis, an old interest of mine, in the radar. The former, America, teaches at Berklee and has a broad overview on market trends; the latter, Italian, teaches in Rome and has become a leading expert of crowdfunding for music projects. I also read a couple of Italian technology blogs.

I am also a faithful reader of two blogs that are not clearly specialized, but are well written and get me to engage with unusual trains of thought. One is that of the British science fiction writer Charles Stross: smart, imaginative and wittily speculative as trhe best science fiction can be. The other one was started relatively recently by Italian economist Tito Bianchi, a sort of Tristram Shandy of economics that moves nimbly from topic to topic in an engaging way. Finally, if you use Google Reader, I suggest you follow engineer and troublemaker Costantino Bongiorno: He is too shy to keep his own blog but he is doing an excellent job of filtering and sharing blogs about hardware hacking, Arduino and related topics.

What about you? Do you have any blog to recommend?