As promised, I have posted a database of variables that I developed for my analyses of the contributions of loans to aid. Also now available is an SQL Server database with the underlying data and logic (You can download the needed software, SQL Server Express, for free but you need to know what you’re doing.)
This database includes a construction of the new DAC ODA variable—which I think you can’t get anywhere else—and my preferred alternatives based on DDRs. All are back-calculated to 1980.
I have also posted a new version of my ODA redefinition paper, “Straightening the Measuring Stick,” which updates last year’s CGD working paper. I presented the newer one last month in Geneva at a conference jointly organized by the IMF and the Graduate Institute Geneva. The proceedings of the conference, including my paper, are now in process with a journal. The largest changes were necessitated by the Development Assistance Committee rule changes agreed in December: rather awkwardly, I had to switch my theme from what the DAC should do to what it had and ought to have done. I blogged the most interesting updates to my thinking in March.
Two intellectual titans are arguing over whether humanity has become less violent. In his 2011 book, Steven Pinker contends that violence is way down since the stone age, or even since the Middle Ages. He looks at murder, war, capital punishment, even violence against animals.
But in a working paper released yesterday, Pasquale Cirillo and Nassim Taleb, the latter the author of The Black Swan: The Impact of the Highly Improbable, contend that Pinker has it wrong. Well, more precisely (lest I incite a riot with demagoguery) they challenge the notion that the great powers have enjoyed a distinctly long peace since World War II.
This paper launches a second round in a war of words (and equations) over the long peace. Previously, Taleb said the The “Long Peace” is a Statistical Illusion. Pinker suggested Taleb was Fooled by Belligerence.
Everything I know about the history of violence, I learned from Pinker’s TED talk. And I have not mastered the mathematical methods marshalled by Cirillo and Taleb. But I do know something about them, having written a program to do them. I think Taleb’s latest salvo mostly misses its mark. Here’s why:
I’ve been reviewing two questions in depth for the Open Philanthropy Project, my 75% employer: How much should we worry about geomagnetic storms? And do alcohol taxes save lives? I hope to share drafts on both soon.
In the meantime, I want to share what is for me a surprising discovery, assuming it is true. The idea that moderate drinking is better for your heart than abstention looks headed for the ash heap of history like so many upended lessons from observational epidemiology. (Years ago, I blogged a certain example of this trend, relating to hormone replacement therapy for post-menopausal women: roughly speaking, observational studies said it was good; randomized trials showed it was not just not good, but bad.)
Here’s a chunk from the draft text that explains how this issue relates to whether alcohol taxes save lives (net), and how I reached my current understanding. I emphasize that I based this write-up on a day or so of reading. That said, my priors about the reliability of studies of various types come from longer experience. I’d welcome critical reactions, and sharing of this post in order to provoke them.
Last year I blogged much about how the Development Assistance Committee (DAC) should revise the definition of Official Development Assistance, particularly in its treatment of loans. Then in December, the DAC members made their decision. Some changes I advocated (though hardly with originality), entered the revised definition of ODA. Others did not. On the day of the announcement I blogged my reactions and some preliminary analysis.
Now I am revisiting this matter as I prepare for an IMF-organized conference next month in Geneva.
Using historical data, I have done my best to apply the new ODA loan rules to historical data. So I can compare ODA computed the new way to ODA computed according to the old way, and to ODA computed in a couple of ways I prefer.
To recap, the DAC decided to:
Just over a year has passed since I hung out my consulting shingle. I have so enjoyed myself: the freedom of being my own boss, the diversity of clients (from Oxfam to the Boston Consulting Group), the variety of work.
But as 2014 drew to a close, I realized that the work I had done for most of the clients was not the stuff of long-term fulfillment; that for me, I came to see, requires being given latitude to delve into a substantial research question that matters, charting my course as I go. One client stood apart in offering the most assignments like that: the Open Philanthropy Project. “Open Phil” is a partnership of the charity evaluator GiveWell, started by Holden Karnofsky and Elie Hassenfeld, and the foundation Good Ventures, co-founded by Cari Tuna and her husband Dustin Moskovitz, himself one of the creators of Facebook. It was for Open Phil that I wrote about whether saving lives causes population growth, whether immigration lowers employment or pay for workers in receiving countries, and how much we should worry about geomagnetic storms (foretaste).
So I decided I’d like to work for them. More…
Years ago when I was building parts of the Commitment to Development Index, I decided to tweak the official computation of countries’ foreign aid spending. It didn’t make sense to me that Net Official Development Assistance (ODA) was “net” of principal repayments received on old aid loans, but not of interest paid on those same loans. As if $1 million flowing from Ghana to Japan had different consequences when it was interest instead of principal… Meanwhile, ODA totals would spike when donors officially recognized losses on aid loans that hadn’t really been serviced in years. Yet writing off loans gone bad didn’t in itself increase transfers from rich to poor nations.
Addressing the first of these concerns was easy. The Development Assistance Committee reports interest received even if it doesn’t subtract it from Net ODA. Addressing the second concern proved surprisingly hard using the information that DAC made available. So I documented both tweaks in a CGD working paper, created a variable called Net Aid Transfers (NAT), and shared the data set publicly.
This graph shows total aid from members of the Development Assistance Committee computed the two ways for 1960-2013, in inflation-adjusted dollars of 2012:
On Sunday I blogged the new Stata program I wrote for applying extreme value theory. It includes a novel computation to reduce bias for the generalized extreme value distribution (GEV). To document the efficacy of that correction and the package as a whole, I set my computer to testing it on simulated data. Since Sunday the little Lenovo has run half a billion regressions.
One topic I’m studying for my main client, the Open Philanthropy Project, is the risk of geomagnetic storms. I hadn’t heard of them either. Actually, they originate as solar storms, which hurl magnetically charged matter toward earth, jostling its magnetic field. Routine-sized storms cause the Auroras Borealis and Australis. Big ones happen roughly once a decade (1972, 1982, 1989, 2003, a near-miss in 2012…) and also mostly hit high latitudes. The worry: a really big one could send currents surging through long-distance power lines, frying hundreds of major transformers, knocking out power to continent-scale regions for months or even years, and causing an economic or humanitarian catastrophe.
My best assessment at this point is that if one extrapolates properly from the available modern data, the risk is much lower than the 12%-chance-per-decade cited by the Washington Post last summer. But that’s a preliminary judgment, and I’m not a seasoned expert. And even if the risk is only 1%, it almost certainly deserves more attention. More from me on that in time. (For a mathematician’s doubts about the 12% figure see Stephen Parrott.)
As they committed to do, the members of the Development Assistance Committee have struck a deal to revise how loans are counted as Official Development Assistance (ODA). They announced it today at the end of their two-day High-Level Meeting in Paris.
The specifics validate the rumors I passed on last month. The benchmark discount rate will be changed from the fixed 10% to the IMF’s new “unified” rate. Now, that rate is 5%. Based on a 10-year moving average of the U.S. 10-year treasury rate, it will plunge to 4% in a little over two years, I estimate, if its formula is followed faithfully. However, I believe that the IMF has not yet committed to updating the rate so mechanically, perhaps because a lower rate would make borrowers’ current debt loads look less sustainable, leaving less room for new lending, to the discomfort of some donor governments. So the DAC has hitched itself to a benchmark whose future is a bit fuzzy.
To the IMF rate will be added a simple risk premium, so that loans will count more as aid when going to countries deemed more likely to default: a 1% premium for upper-middle-income countries (UMICs), 2% for lower-middle-income countries (LMICs), and 4% for low-income countries (LICs). As it happens, the IMF’s sibling, the World Bank, curates this three-way classification of developing countries, which is effectively annexed to the statistical definition of aid.
After two years of communiqués, consultations, and commentary, the Development Assistance Committee has gotten down to brass tacks in fixing the definition of Official Development Assistance (ODA). I hear that a negotiating group composed of key donor representatives named for its chair, the UK’s Mark Lowcock, has reached a tentative deal. The Lowcock group’s role being unofficial, DAC chair Erik Solheim has turned its consensus into a proposal for discussion with the entire DAC membership.
I have not seen the document, so I cannot report definitively on it. It appears purely focussed on the issue that forced the discussions in the first place, which is when and how much to count loans as aid. I gather that the principle elements of the compromise are:
This morning, one of my key secret intelligence sources (code name: MOM) alerted me to the appearance of a big New York Times exposé of foreign-government funding for U.S. think tanks seeking to influence domestic policy.
The article starts this way:
The agreement signed last year by the Norway Ministry of Foreign Affairs was explicit: For $5 million, Norway’s partner in Washington would push top officials at the White House, at the Treasury Department and in Congress to double spending on a United States foreign aid program.
But the recipient of the cash was not one of the many Beltway lobbying firms that work every year on behalf of foreign governments.
It was the Center for Global Development, a nonprofit research organization, or think tank, one of many such groups in Washington that lawmakers, government officials and the news media have long relied on to provide independent policy analysis and scholarship.
My client GiveWell, working closely with the foundation Good Ventures through the Open Philanthropy Project, is seriously considering labor mobility as a cause to which Good Ventures should commit resources:
It appears to us that moving from a lower-income country to a higher-income country can bring about enormous increases in a person’s income (e.g., multiplying it several-fold), dwarfing the effect of any direct-aid intervention we’re aware of.
But there are worries: Does letting more workers into a wealthy country take jobs from people already working there? Or does the competition for jobs reduce wages all around? These possibilities are a particular concern as they apply to low-skill workers, who are poorer.
For due diligence, GiveWell hired me to review the evidence on the potential side effects of immigration. Here is my full report, ready for comments from anyone. To read my conclusion, skim down to the bullet points.
In March I recounted how former colleagues Michael Clemens, Steven Radelet, and Rikhil Bhavnani wrote an excellent paper in 2004 on the impact of foreign aid on economic growth, “Counting Chickens When They Hatch.” The idea captured in that title is that it is important to think about the likely timing of the impacts of aid. Don’t design your analysis as if you expect that funding for teaching 6-year-olds will raise economic growth in four years. Match the follow-up period to the type of aid. Count your chickens only when they hatch.
Some years later, and joined by another CGD recruit, Samuel Bazzi, those authors overhauled their paper and published it in the top-flight Economic Journal (ungated version). The final version is quite different but also excellent (it won the journal’s best-article prize). Instead of doing its own econometrics afresh, it modifies the three most-cited studies in the aid-growth literature in light of the “counting chickens” insight. Although those studies disagree on whether and when aid “works,” in the sense of boosting growth, Clemens, Radelet, Bhavnani, and Bazzi (CRBB) conclude that revising the studies to take timing into account causes all results to converge, to a ginger but positive appraisal. (Listen to Michael speak cautionarily about “Chickens” in this Library of Economics and Liberty podcast.)
I say “excellent” and I mean it. But, true to type, I actually doubt the econometric reasoning. I am not persuaded by these results that “aid inflows are systematically associated with modest, positive subsequent growth.” More…
The last of my three posts for CGD on redefining Official Development Assistance (ODA) tries to get away from the loan business (which has gotten most of my attention and is the reason the definition of ODA is up for discussion at all). In the new post I talk about what activities ought to dropped from or added to the definition in order to keep it credible and up to date.
The April issue of the Journal of Development Studies includes the final version of my article with Jonathan Morduch replicating the study of the impact of microcredit in Bangladesh by Mark Pitt and Shahidur Khandker. Properly, the journal also carries a reply from Mark Pitt. (Ungated versions of the dueling documents are here and here.) To my surprise, JDS did not solicit a rejoinder from us the way they did in a nearly identical situation involving a JDS editor as replicating author. Perhaps this is a sign of the strength the editors see in our paper…which is to say, maybe I should have just chilled.
But as usual, Pitt’s arguments are strongly worded even as their subject remains technical. So the average reader will absorb the style more than the substance, and wonder, I fear, who are these fools Roodman and Morduch? So for the public record, here is a rejoinder from yours truly. It’s a quote-and-response.
“RM [Roodman & Morduch] have backed off many of their prior claims and methods.”
No. The first version of our paper questions the exogeneity of the core intent-to-treat variables; highlights that an asserted discontinuity in treatment, central to Pitt & Khandker’s (PK’s) claim to quasi-experimental status, is absent from the data; observes that the magnitude of the impact estimates depends on an arbitrary censoring choice for the “log of 0”; and demonstrates that a more-robust linear estimator produces no evidence of impact. Those arguments stand.
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