Entries tagged with “Paul Collier”.


An interesting review of Paul Collier’s The Bottom Billion and Wars, Guns and Votes by Yale Anthropologist Mike McGovern has gotten a little bit of attention recently in development circles, speaking as it does to ongoing debates about the role of statistical analysis, what counts as explanation, and where qualitative research fits into all of this.  I will take up McGovern’s good (but incomplete, in my opinion) review in another post.  Here, I needed to respond to a blog entry about this review.

On the Descriptive Statistics, Causal Inference and Social Science blog, Andrew Gelman discusses McGovern’s review.  While there is a lot going on in this post, one issue caught my attention in particular.  In his review, McGovern argues that “Much of the intellectual heavy lifting in these books is in fact done at the level of implication or commonsense guessing,” what Gelman (quoting Fung) calls “story time”, the “pivot from the quantitative finding to the speculative explanation.”  However, despite the seemingly dismissive term for this sort of explanation, in his blog post Gelman argues “story time can’t be avoided.” His point:

On one hand, there are real questions to be answered and real decisions to be made in development economics (and elsewhere), and researchers and policymakers can’t simply sit still and say they can’t do anything because the data aren’t fully persuasive. (Remember the first principle of decision analysis: Not making a decision is itself a decision.)

From the other direction, once you have an interesting quantitative finding,of course you want to understand it, and it makes sense to use all your storytelling skills here. The challenge is to go back and forth between the storytelling and the data. You find some interesting result (perhaps an observational data summary, perhaps an analysis of an experiment or natural experiment), this motivates a story, which in turn suggests some new hypotheses to be studied.

Now, on one hand I take his point – research is iterative, and answering one set of questions (or one set of new data) often raises new questions which can be interrogated.  But Gelman seems to presume that explanation only comes from more statistical analysis, without considering what I saw as McGovern’s subtle point: qualitative social scientists look at explanation, and do not revert to story time to do so (good luck getting published if you do).  We spend a hell of a lot of time fleshing out the causal processes behind our observations, including establishing rigor and validity for our data and conclusions, before we present stories.  This is not to say that our explanations are immediately complete or perfect, nor is it to suggest that our explanations do not raise new questions to pursue.  However, there is no excuse for the sort of “story time” analysis that McGovern is pointing out in Collier’s work – indeed, I would suggest that is why the practice is given a clearly derisive title.  That is just guessing, vaguely informed by data, often without even thinking through alternative explanations for the patterns at hand (let alone presenting those alternatives).

I agree with Gelman’s point, late in the post – this is not a failing of statistics, really.  It is a failure to use them intelligently, or to use appropriate frameworks to interpret statistical findings.  It would be nice, however, if we could have a discussion between quant and qual on how to avoid these outcomes before they happen . . . because story time is most certainly avoidable.

Andy Sumner and Charles Kenny (disclosure – Andy and Charles are friends of mine, and I need to write up my review of Charles’ book Getting Better . . . in a nutshell, you should buy it) have a post on the Guardian’s Poverty Matters Blog addressing the two most recent challenges to the idea of the “poverty trap”: Ghana and Zambia’s recent elevations to middle-income status (per capita GNIs of between $1,006 and $3,975) by the World Bank.

Quick background for those less versed in development terminology: GNI (Gross National Income) is the value of all goods and services produced in a country, as well as all overseas investments and remittances (money sent home from abroad).  Per capita GNI divides this huge number by the population to get a sense of the per-person income of the country (there is a loose assumption that the value of goods and services will be paid in the form of wages).  So, loosely speaking, a per capita GNI of $1006 is roughly equivalent to $2.75/day.  Obviously $2.75 buys a lot more in rural Africa than it does basically anywhere inside the US, but this is still a pretty low bar at which to start “Middle Income.”

I do not want to engage an argument about where Middle Income should start in this post – Andy and Charles take this up near the end of their post, and nicely lay out the issues.  The important point that they are making, though, is that the idea that there are a lot of countries out there mired in situations that make an escape from food insecurity, material deprivation, absence of basic healthcare, and lack of opportunity (situations often called “poverty traps”) is being challenged by the ever-expanding pool of countries that seem to be increasing economic productivity rapidly and significantly.  The whole point of a “poverty trap”, as popularized by Paul Collier’s book on The Bottom Billion and Jeffrey Sach’s various writings, is that it cannot be escaped without substantial outside aid interventions (a la Sachs) or may not be escapable at all.  Well, Ghana certainly has received a lot of aid, but its massive growth is not the product of a new “big push”, a massive infusion of aid across sectors to get the country up into this new income category.  Turns out the poorest people in the world might not need us to come riding to their rescue, at least not in the manner that Sachs envisions in his Millennium Villages Project.

That said, I’ve told Andy that I am deeply concerned about fragility – that is, I am thrilled to see things changing in places like Ghana, but how robust are those changes?  At least in Ghana, a lot of the shift has been driven by the service sector, as opposed to recent oil finds (though these will undoubtedly swell the GNI figure in years to come) – this suggests a broader base to change in Ghana than, say, Equatorial Guinea . . . where GNI growth is all about oil, which is controlled by the country’s . . . problematic . . . leader (just read the Wikipedia post).  But even in Ghana, things like climate change could present significant future challenges.  The loss of the minor rainy season, for example, could have huge impacts on staple crop production and food security in the country, which in turn could hurt the workforce, exacerbate class/ethnic/rural-urban tensions, and generally hurt social cohesion in what is today a rather robust democracy.  Yes, things have gotten better in Ghana . . . but this is no time to assume, a la Rostow, that a largely irreversible takeoff to economic growth has occurred.  Aid and development are important and still needed in an increasingly middle-income world, but a different aid and development that supports existing indigenous efforts and consolidates development gains.