African Studies Meetings in San Diego 19-22 Nov 2015

I am really looking forward to the annual African Studies meetings in San Diego.

(The preliminary program is here: The State and the Study of Africa, November 19-22, 2015. San Diego, California).

I will be giving two papers. I give one paper on Friday morning in “State Building, States, and State Transformation in Africa: Legacies, Impacts, Consequences and Solutions” (Friday, Nov 20, 8:30-10:15am, V-P-2) and then a second paper at the ASA Roundtable on Methods Saturday November 21 8:30-10:15. I will be speaking on studying Africa by numbers.

I will also be giving an informal presentation of my book. Join me at the University of Chicago Press booth (#305) on Saturday, 4 PM for some wine and a chat about “Africa: Why Economists Get It Wrong“.

ASA jerven book talk

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Power of indicators: an emerging literature

There is a rise of indicators. The so called data revolution is finding its feet, so I  do not expect it to let up anytime soon.  The Economist provided one overview in their report on ‘How to lie with indices‘.


As one would expect there is now a ballooning literature to match the rise of indicators. The early and leading contributions in this literature emerged from  Law and Anthropology (sometimes cross-disciplinary work), but now International Relations and Political Science is following. Economics is as far as I can tell still on the sidelines.  Anthropology and ‘Constructivism’ within International Relations has a natural comparative advantage in approaching data as social products. On the other hand, economists, statisticians and political scientists of the positivist mold, have a mountain to climb.

I hope there will be a gradual shift in all disciplines towards approaching indicators critically as ‘products’ rather than the mainstream approach of being uncritical consumers of indicators. All these indicators are entering the realm of ‘as if’ governance.

We all know, I hope, that the Freedom House actually does not measure ‘democracy’;  that the Consumer Price Index does not actually measure ‘inflation’; nor does Transparency International actually measure ‘corruption’. We just pretend ‘as if’ they do. We are in deep trouble if we forget that we are making decisions or doing analytic research ‘as if’ these things could actually be counted.

Despite the many publications I think there are still many holes in our knowledge. There is a further need for empirical research on the lines of ‘political ethnography of indicators’. Particularly is there a gap in theory and empirical studies on the line of causality from ‘data’ to ‘decisions’. There is also a surprising gap on knowledge of what makes a good indicator, and what does not.  Here’s a sample of books coming in 2015 and 2016.

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Book Talk: Africa – Why Economists Get it Wrong @SAISAfrica OCT 7, 5PM

SAIS Jerven


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Book Talk: Africa – Why Economists Get it Wrong @TheNewSchool OCT 9 2:30 PM

New School Jerven

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Book talk: Africa: Why Economists Get it Wrong #LSE Friday 18 Sep, 6 PM


The event is free to attend, and there will be refreshments. There will also be copies of the books for sale.

I will also discuss isues covered in my book on Wednesday 23 September at 1pm at the Overseas Development Institute.  The event is called: Understanding economic transformation in Africa. There is an impressive line up of commentators and speakers: Blandina Kilama - Senior Researcher, REPOA, Tanzania, Nick Crafts – Professor of Economics and Economic History at the University of Warwick and Louise Fox – Visiting Professor, University of California, Berkeley. The event is chaired by Dirk Willem te Velde - Director, Supporting Economic Transformation, ODI.

Want to prepare yourself with some clever comments from recent book reviews? Africa: Why Economists Get it Wrong was reviewed the Africa at LSE blog, in the Financial Times and in the Washington Post’s Monkeycage blog last week. The International Development blog at LSE also wrote about the book here.  Quoting from Laura Seay and Kim Yi Dionne‘s review here:

Jerven’s book is controversial and has already provoked debate. His points are elegantly argued and although he delves into extremely technical economic concepts and methods, “Africa: Why Economists Get It Wrong” is readable and easy for a nonspecialist to understand. But specialists in particular must read Jerven, and take seriously his claims.

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Book Reviews: Africa. Why Economists Get It Wrong

The response to my book has been an overwhelmingly positive. I always knew it would divide opinion. Alex De Waal did perhaps provide the most encouraging and ringing support with a review titled “Liberating African Economic History from the Tyranny of Econometrics

Africa: Why Economists Get it Wrong is a slender but important book. It is a charter for liberating African economic policymaking from the tyranny of econometricians.

Ian Scoones, Jeff Bloem, and Ken Opalo all wrote very nice reviews, and Opalo summarized it neatly in a tweet:

I was thrilled to see that the Economist reviewed it and followed up by a nice set of tweets.

I wrote something about the book for New African Magazine. If you want a taste of the introduction – go here – if you need to read an excerpt of the conclusion – click this – and if you want to hear me talk about the book you can pick between Owen Barder at Development Drums or Russ Roberts at Econtalk.  

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Why did economists spend two decades explaining something that never happened ?

For the past two decades, mainstream economists who study African economic growth have been trying to explain something that never happened. Economists have focused almost exclusively on one question: Why has economic growth failed in Africa?

You can read the motivation for my book in a post I wrote for African Arguments here. I have discussed the book on two podcasts – with Russel Roberts on Econtalk here, and with Owen Barder on Development drums here.

In the podcast and the book I say that the bottom line is that there is no bottom billion. The graph below should make that case quite clear. Mainstream economists ignored growth in the 1960s and 1970s, and disregarded recent growth, and have sought to explain a phenomena that only partly holds true in the 1980s.  That’s the motivation for chapter 1 in the book. In chapter two I show how the stylized fact of ‘chronic failure’ made the basis for a literature that simply focused on explaining ‘why nations fail‘. In chapter three I show that it is better to approach economic growth in Africa as recurring rather than failed, and in chapter four I show how scholars and institutions continue to get their analysis of ‘Africa Rising’ wrong, because they are not doing their homework when it comes to questioning the data and the data sources.Capture


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Book Launch: Africa: Why Economists Get It Wrong

On June 4 at 6 pm I will present my latest book at SOAS in London, UK. The title is Africa: Why Economists Get It Wrong. Jerven_AfricaWEGIW_Visuals_1#10

In four chapters I deliver a critique of how mainstream macroeconomic literature has sought to explain economic growth in Africa.


You can read more editorial blurbs here, but let me quote two from William Easterly and James Ferguson.

‘A highly readable and absolutely devastating critique…Jerven argues convincingly that a better understanding can be obtained by setting aside the “African failure” frame.’ – James Ferguson, Stanford University

‘Jerven brings a healthy scepticism to economists’ pronouncements about Africa. This book should be required reading for anyone who cares about African development.’ – William Easterly, author of The Tyranny of Experts

If you are in London, remember to register for the launch here. The book is already available on and I expect the book to be in stock elsewhere very soon.


Posted in Africa Rising, Africa: Why Economists Get It Wrong, African Economic History, Booktalk, Economic Growth, Economics, History, Zed | Tagged , , , , | 1 Comment

A reading list for the data revolution

If you have sat through more than two conferences and workshops on the post-2015 development agenda or the Sustainable Development Goals (or tracked #SDGs or #data2015 on Twitter) you will be aware that there is a certain repetition of ideas. The same soundbites are recycled, and one report seemingly feeds off the other. I have compiled a list of  books that may help you think outside the box if you are writing and thinking about the ‘data revolution’ in development.

1. Statistics and the German State, 1900-1945: The Making of Modern Economic Knowledge by J. Adam Tooze – they are talking about a ‘data revolution’, but when was the ‘statistics revolution’? Tooze takes us to the optimism in the German statistical office when they thought all could be counted and known, and how enthusiasm was curbed ever so slightly by the regime that appeared in the 1930s.
2. Trust in Numbers. The Pursuit of Objectivity in Science and Public Life by Theodore M. Porter – ever wondered why we almost without question accept metrics such as inflation, total population when they are arbitrary, soft and sometimes manipulated? Well, objectivity is a social and political product. Equally good is The Politics of Large Numbers: A History of Statistical Reasoning by Alain Desrosières.
3. How to Lie with Statistics by Darrel Huff – there are a number of books out there on how to spot how actors deliberately manipulate statistics, and use them as rhetorical devices. A large dose of skepticism is needed in these days to avoid getting carried away with all the fancy data visualizations.

4. Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schönberger and Kenneth Cukier – there are plenty of competing books on the world of big data. This is the best survey on the general issues in my mind. A bit celebratory, but with the other books on this list you will keep a healthy skeptical mind.
5. Registration and Recognition: Documenting the Person in World History by Simon Szreter & Keith Breckenridge – so you thought that states counted people because they want to know how they can help them? Think again. Excellent global historical survey of registration systems.
6. Biometric State: The Global Politics of Identification and Surveillance in South Africa, 1850 to the Present by Keith Breckenridge – ever wondered why the most advanced country in registration and biometrics is South Africa?

7. Africa as a Living Laboratory: Empire, Development, and the Problem of Scientific Knowledge, 1870-1950 by Helen Tilley – so you thought that it was a new idea that an alliance of experts gathered in western cities decided that all we needed was to collect more data, and then we would solve their problems. Think again. A good companion to Easterly’s The Tyranny of Experts.
8. The Economist’s Tale: A Consultant Encounters Hunger and the World Bank by Peter Griffiths – a bit nuts, but never boring, Griffiths describes the classic problem of the consultant that needs write a report on a critical problem, but facts and numbers are soft or missing entirely. Another classic in the genre is Tropical Gangsters and I also like Stolper’s Planning without Facts.
9. The Anti-Politics Machine: Development, Depoliticization, and Bureaucratic Power in Lesotho by James Ferguson – the classic critique of the technocratic approach to economic development, and particularly good at showing how global categories and standards don’t match with the local situation. The classic statement was made by Polly Hill in her Development Economics on Trial: The Anthropological Case for a Prosecution.

If you want to know how economic statistics in some African countries are produced, and how they are disseminated by international organizations and how they are misused by analysts and research, look no further. Since the publication of Poor Numbers: How We Are Misled by African Development Statistics and What to Do about It I have also published a more detailed study of what happened to to the economic growth evidence in Botswana, Kenya, Tanzania, and Zambia, 1965-1995. Even more recently, I edited volume on Measuring African Development: Past and Present, which I recommend highly, together with a special issue in the Journal of Development Studies on the African Statistical Tragedy (Ungated access here, and you can access the papers in the other volume here).

There is a rapidly emerging literature on the use of global indicators, see here for a list of five books being published in 2015.

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What did we learn from measuring the costs of monitoring the SDGs?

In response to my costing estimate of the MDGs, UN Sustainable Development Solutions Network took the initiative to host a group of ‘experts’ to come up with a collective estimate. The group first met in October in Paris and New York, and the final report was published on April 17. The objective of the process and the report varied. Some had the their eyes firmly on the man: providing a ‘useful number’ for the Financing for Development Conference in Addis, while others watched the ball: trying to get as objective cost estimate as possible. What did we learn from the process and the report?

1. The numbers are soft. Very soft.

Ultimately the total number in any such exercise will depend on the multipliers. A survey has a ballpark per household cost. You can use the low end or the high end. Then multiply that with the number of households. Multiply that with the number of countries (193? 139? 77?), and then multiply that with the frequency (Monthly? Quarterly? Annual? Every ten years?). Depending on your requirement you can generate any kind of total number. My advice is to read the report with that in mind. Disregard the headlines, and look at the detail.

2. Annual disaggregated statistics on all indicators are not feasible.

Ultimately we dropped calculating for all countries (only 77) and perhaps most notably, we dropped the ambition of having annual disaggregated survey data. The sample size requirements of having disaggregated data by region, gender, age and what not category is daunting. And remember this. Annual survey data with current survey instruments is not feasible. For poverty data a survey takes 2-3 years from start to end – without completely re-visioning current informational infrastructure such a survey burden is to heavy to carry for a statistical office that has other tasks than reporting on SDGs alone.

3. Want open data? Start with the costs of data.

As I detail in my paper, it is very hard to get actual costs of surveys and censuses. To sift through background documents to find the costs is time consuming, and if you send queries to organizations that do these surveys you can expect generic responses, or that  “we do not share specific cost estimates”. The survey business is a survey business, and detailed cost information today is competitive edge in a bidding process tomorrow. Moreover, to get individual country budget information, on either donor or recipient side, on how much is actually spent on data is difficult.

4. The bottleneck is not funding, but capacity.

If you would ask the technical assistance teams at IMF or the statistical capacity teams at the World Bank how much it would cost to ‘mend the gaps’ in statistical capacity in low income countries, they would reply to you that the problem is not how much you can spend, but how much can be absorbed. International organizations and donors can buy a nice data-set, or send an expert well versed in the international standards of accounting, There needs to be domestic capacity jut to handle receiving the funds and the experts, let alone benefiting from it.

5. Looking like a donor versus looking like a state.

The report is looking like a donor. It is easier to find costs on a survey, but hard to find information on what it would entail to improve administrative statistics. Moving forward we need to keep in mind that monitoring and data is not a goal in itself. Donor decisions and reports matter less, what is important is the quality of the data feeds into decisions at country level. If our focus is mostly monitoring global progress that might actually hamper domestic political accountability.

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