Statistical Tragedy in Africa? Evaluating the Data Base for African Economic Development

On Monday, April 6, 2015 – 10:00am to 11:30am the special issue in the Journal of Development Studies: Statistical Tragedy in Africa? Evaluating the Data Base for African Economic Development which I edited with Deborah Johnston is being launched at the Center of Global Development in Washington DC.

Statistician General, National Bureau of Statistics in Nigeria, Yemi Kale and I will both give a keynote. The event is organized and introduced by Amanda Glassman, and a panel discussion in Francisco Ferreira, Chief Economist, World Bank Africa and and Roberto Rosales, Deputy Director, Statistics, International Monetary Fund will follow.

You can register for the event here.

The special issue is the second set of papers following the 2013 conference in Vancouver, where Poor Numbers: How We Are Misled by African Development Statistics and What to Do about It was launched. The first set of papers was published in the Canadian Journal of Development Studies, and are also available as a book with Routledge. The special issue: Measuring African Development: Past and Present is currently freely available.

Below, find the table of contents to the special issue in Journal of Development Studies – which can be accessed here (ungated until 30th of June, 2015).toc-jds jerven & johnston

Posted in Africa Rising, Africa's Statistical Renaissance, Africa's Statistical Tragedy, African Development Bank, Agriculture, Canadian Journal of Development Studies, IMF, Measuring African Development: Past and Present, Poor Numbers, Poverty, World Bank | Tagged , , , , , , , , , , , , , , | Leave a comment

Call for papers WEHC 2015: Counting people, understanding economies: global histories of registration and demographic statistics

Gerardo Serra (Sussex) and I are issuing a call for papers for the panel on ‘Counting People, Understanding Economies: Global Histories of Registration and Demographic Statistics’ that we set up for the forthcoming World Economic History Congress in Kyoto (3-7 August 2015).

Interested contributors should contact Gerardo with the title and abstract of the proposed paper by the end of March. 

The abstract of the panel can accessed here.

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Africa and Economics. What’s the problem?

Sensitivity to local conditions? Check. World Bank Kenya got it covered.

Right on cue, the World Bank makes a contribution to the debate on whether Economics has an Africa problem (here and here).

(HT: @g33kmate)

It might be that Africa has an economics problem. That is the subject of my next book: Africa: Why Economists Get It Wrong.

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“Does economics have an Africa problem?” – A rejoinder

Does Economics have an Africa problem? Yes, says Griewe Chelwa in a post for the blog Africa is a Country. Chelwa points out that the most important conferences on African economic development routinely are organized outside of Africa. He also notes that this extends to the composition of editorial boards of journals. Both the Journal of Development Economics and the Journal of African Economies are guilty of having no members on their editorial boards who are based in Africa. Chelwa’s conclusion is devastating: “Economics as a discipline is sending a clear message: Africa cannot be a leading participant in the debates that ultimately shape its destiny.”

I offer my reflections in a post for African Arguments. Among other things I suggest that

it matters more how studies are done rather than who did them. I think that the economic discipline is guilty of doing research on Africa that ignores local context and is lacking in policy relevance. Moreover, as Gareth Austin has pointed out, because most models of economic development are derived from studies on Europe and the West, the toolbox of economists is conceptually Eurocentric. This is the subject of my forthcoming book: Africa: Why Economists Get It Wrong.

Read the full post here.

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Public talk in Bordeaux 19 FEB 6 PM: Derrière “l’émergence de l’Afrique”. La croissance, une fiction statistique ?

bordeaux

I am a visiting scholar at “Les Afriques dans le monde” at  Sciences Po Bordeaux in the spring term 2015. This event is public and free, it is organized by Vincent Bonnecasse – who contributed a chapter in my recent edited volume. There are three speakers: Jean-Phillippe Berrou, Boris Samuel (who wrote a chapter on Mauritania in my most recent book) and yours sincerely.

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Podcast: How poor numbers undermine the fight against poverty

It is two years since Poor Numbers was published, and I had a nice conversation with Tom Paulson and Gabe Spitzer at Humanosphere. You can listen to the podcast here. We talked about the importance of getting good evidence, but also on the impact the book had and why it also caused some controversy.

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Just Published: Measuring African Development: Past and Present

Very happy to the see Measuring African Development: Past and Present in print. You can read an open access of the introduction to the book here.  The volume takes you through the very first household budget surveys and national account estimates during colonial rule up through contemporary efforts of improving data with mobile phones, GPS and handheld devices.

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Posted in Africa's Statistical Renaissance, Africa's Statistical Tragedy, African Economic History, Agriculture, Canadian Journal of Development Studies, Christopher Cramer, Gerardo Serra, Ghana, IMF, Measuring African Development: Past and Present, Population, Routledge, Sudan, Tanzania | Tagged , , , , , , , , , , , , , , , , | Comments Off

IMF and Ebola: why we don’t have any good answers

The debate on whether IMF has any blame for Ebola has been frustrating, even infuriating. It is going to continue to be frustrating largely because: “Who is to blame for Ebola?” is really not a good question. In turn, we have not got good answers.

  1. IMF is to blame.

That’s a bad answer. And that’s the how many, including Chris Blattman summarizes the view taken by the authors of the Lancet piece.  But Kentikelenis, King, McKee and Stuckler carefully stated “it could be that the IMF had contributed to the circumstances that enabled the crisis to arise in the first place”. It should be noted that it was provoked by the IMFs announcement of US$ 430 million of funding to fight Ebola. The IMF was selling itself as the solution to Ebola. But you could plausibly argue that IMF was part of the problem as well.

  1. History and Institutions is to blame.

That’s the view taken by Blattman in his first response. It is about state capacity, and it is wrong to assume that Africa is a blank slate. He is implicitly evoking the economic growth and political science literature that argues that the reasons why ‘good’ or ‘bad’ external policy advice makes little sense in countries like Sierra Leone, Liberia and Guinea. I am not that impressed with the research this argument relies on. Sure, according to the regression results – high ethnic fragmentation, colonial institutions, geography, slave trade, just to mention a few – is correlated with ‘bad’ institutions, ‘bad’ policy and low income per capita today.

I got two main problems with this. One is that it carries the ‘why aren’t you more like Denmark’ policy implication. Second, it is often forgotten that if you read the regression results there is only a fraction of the development outcomes today that is explained by ‘historical’ factors. I do sympathise with the view that is wrong to ignore politics and history – but I think that the literature that warns against the blank slate approach is equally wrong about ignoring the fact that recent history and current actions do actually have decisive impacts. The causality is messy, and because it is cleaner econometrically, messy current day politics is treated as an outcome. Yes, the answer is in politics and history, but IMF plays a role in that history.

  1. IMF is not to blame.

I could not make up a weaker response for the IMF than the one they came up with. They ran some econometric tests (with the fiscal data they themselves help country authorities to aggregate by the way) – et voilà: “we find an increase in health spending as a percent of GDP. In Guinea, spending increased by 0.7 percentage points, in Liberia by 1.6 points and in Sierra Leone by 0.24 points (from 2010 to 2013).”

0.24 percentage points? Really? So in Sierra Leone, according to World Bank statistics, total health spending as a share of GDP (note that this is not public, but total) was 15.24 percent in 2010 and it was 15.08 percent in 2012, the World Bank does report 2013 yet. In my experience with error margins in official statistics like this (remember, the denominator is GDP which can be a bit wobbly), that is not enough to assert direction of change. Look here, what happens to health spending as a share of GDP according to World Development Indicators.

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The pattern is stagnation. We start at 15 percent in Sierra Leone and end up at 15 percent. We start at 6 percent in Guinea and we end up with 6 percent. That’s the end of the civil war. So to find a percentage fraction in this history and say: ‘look that’s me’, is not a good answer.

Towards a better question:

Obviously I agree with Blattman in that one needs to take into the opportunity costs when making statements about how much should be spent. I also agree that we need better research to get better answers. The ones I reviewed here are all pretty sloppy, but the original question that actually should be posed is whether the Ebola crisis have shown that over the past decades IMF focus a bit too much on fiscal discipline and too little on the importance of capacity in education and health. Most agree that too much was cut in the 1980s and 1990s, and there bits and pieces of evidence that Kentikelenis, King, McKee and Stuckler can point to show that the priority given to increasing capacity to deliver health services Sierra Leone, Liberia and Guinea is not high enough.

Final note: In all this I was reminded by the excellent book by Griffiths on Sierra Leone in 1986. Worth a read.

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Writing about a data revolution: A critique in four venn diagrams

The UN Secretary-General’s Independent Expert Advisory Group on a Data Revolution for Sustainable Development (IEAG) have completed their report.  “A world that counts” is a cleverly crafted motivational manifest.  But it is not a practical roadmap on how to apply a ‘data revolution’ to the sustainable development goals agenda. The report’s key weakness is that it conflates a lot of terms, and assumes automatic relationships between things like ‘counting’ and ‘knowing’. I write about it in more detail here.  The mistakes made in the report are fundamental. Here I show some of the basic conflations in terms in four diagrams.

Not everything that counts can be counted

stuff that counts

The report strongly suggests that everything that matters can be counted. We know that this is not true. If the guiding principle for the Sustainable Development Goals is to make decisions ‘as if’ everything can be counted, the end result will be very misleading.

Data is not the same as statistics

 

stuff that counts

The data revolution hype is just one of many places where ‘statistics’ and ‘data’ are conflated. Data is not the same as numbers. Data literally mean ‘what is given’, so when we speak of data we are talking about observations – quantitative or qualitative, even figurative that can be used to get information.

To keep talking about data when we mean statistics may sound better, but it only contributes to confusion. The report suggests that the UN should develop a ‘global consensus on data’. What is that supposed to mean? That statement is meaningless if you exchange the word ‘data’ with ‘observations’, ‘knowledge’ or ‘evidence’. It can however make sense if you talk about ‘statistics’.  International organizations do have a natural role when it comes to developing global standards for official statistics.  Reaching a global consensus on how observations and evidence constitute knowledge is futile.

There are more methods to knowing than through counting

stuff that counts 3

The report says (p. 2-3): “whole groups of people are not being counted and important aspects of people’s lives and environmental conditions are still not measured” and then that “Never again should it be possible to say “we didn’t know”. No one should be invisible. This is the world we want – a world that counts.”

I understand the enthusiasm, but I want to warn against hubris. This is certainly not the world I want. I think it should always be possible to say ‘we didn’t know’. Numbers, or the act of counting does not guarantee objectivity nor does it always make us wiser.  It is a testament to the richness of life, and the poverty of numbers that all things cannot be counted.

More data does not mean better decisions

stuff that counts 4

The report says that demanding more data will lead to better decisions. That is a statement of belief, not a a theory of of change. What is often thought of as ‘evidence-based policy’ turns out to be ‘policy-based-evidence’. In short, predominantly the causality runs from policy to statistics. And a lot of evidence does not inform policy at all – whereas a lot of decisions are made without or despite data. That begs the question - how much resources should one advocate that is spent on a global development monitoring framework?

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Africa: Why Economists Get It Wrong

My latest book is available for pre-order:

For the first time in generations, Africa is spoken of these days with enthusiastic hope: no longer seen as a hopeless morass of poverty, the continent instead is described as “Africa Rising,” a land of enormous economic potential that is just beginning to be tapped.

With Africa: Why Economists Get It Wrong, Morten Jerven offers a bracing corrective. Neither story, he shows, is accurate. In truth, most African economies have been growing rapidly since the 1990s—and, until a collapse in the ’70s and ’80s, they had been growing reliably for decades. Puncturing weak analysis that relies too much on those two lost decades, Jerven redraws our picture of Africa’s past, present, and potential.

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