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


Posted in Africa Rising, Africa: Why Economists Get It Wrong, Booktalk, Economic Growth, Economic History, Economics, Podcast, Poor Numbers | Tagged , , , , , | Comments Off

Book Launch: Africa: Why Economists Get It Wrong

On June 4 at 6 pm I will present my latest book at SOAS in London, salve 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, rx 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, buy 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 the emerging literature on the power of indicators.

Posted in Africa's Statistical Tragedy, Book review, Data revolution, Economic Growth and Measurement Reconsidered, MDGs, Measuring African Development: Past and Present, National Accounts, Nigeria, Poor Numbers, SDGs, South Africa, World Bank | Tagged , , , , , , , , , , , , | Comments Off

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.

Posted in Data revolution, MDGs, ODI, PARIS21, SDGs, United Nations | Tagged | 1 Comment

Development by Indicators: Knowledge and Governance

In this workshop organized at Nantes by Boris Samuel and me on May 5 and 6, view 2015 we will investigate the role of indicators in economic development. We will explore how numbers structure knowledge about economic development and how they give rise to social and political processes. Finally we will also shed light the on the importance of numbers for the day-to-day operations of economic development and for global governance.

The questions will be organized under three main umbrellas:

1. Numbers in mobilization: From MDGs to SDGs

There is a need to reflect on where the quantification in development is taking us. The success of quantifiable targets sometimes overshadows the significance of unquantifiable aspects of economic development. The effects of the growing use of indicators in mobilizing for development, cheap and the proliferation of indicators need also to be questioned.

2. Numbers for governance: Ruling by numbers

Are statistics a part of the façade of operating international economic development, or are we really seeing ‘evidence based policy’ in economic development? Are there identifiable benefits of good data and costs of bad data? Which are social and political processes based on the inflation of indicators? Are there any unintended consequences for local development introduced by using global indicators of development?

3. Measuring and governing poverty

What do we know about the poor?  We will address this question by studying the process of defining, measuring and then taking action about aspects of poverty. How does information flow from ‘the poor’ to the informational centers of the world?

The full program is here. Mary Morgan is giving the keynote. It is free to attend for those who register.  Also, for those who are doing work on indicators and their role in development, note this interesting looking call for papers here.

Posted in Data revolution, Gerardo Serra, History, Poor Numbers, Poverty, SDG, Workshop | Tagged , , , , , , , , , , , , , | Comments Off

Why so grumpy? The datarevolution and its discontents

In “Big Questions for Big Data and what it can do for African Economic Development” I wrote about some of the basic knowledge problems that remain in development statistics, and concluded that, as of yet, Big Data does not seem well equipped in addressing these. I got two kind of grumpy twitter responses from the Open Data Watch and Claire Melamed, who really don’t appreciate if you question the wisdom of the tagline in the data revolution report: a world that counts.

It is not the first time we had a debate on this – see the comment section in the piece I wrote for the Guardian. So what are those sentences?

“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.”

So for the record, I fundamentally disagree with these sentences. It should always be possible to say that we did not know, to think that we can count everything and therefore know everything is fundamentally wrong. These are not three obscure sentences, it is the tagline of the report, setting out the spirit of the ‘data revolution’. At best this is naive, at worst, it is dangerously misleading.

Posted in Data revolution, MDGs, Poor Numbers, SDGs, Uncategorized | Tagged , , | 1 Comment

Statistical Tragedy in Africa? Take 2

The launch of the special issue in the Journal of Development Studies took place at the Center of Global Development today. All the papers are available free here.

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

On Monday, salve April 6, thumb 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 , , , , , , , , , , , , , , | Comments Off

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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