Author Archives: Olumide Abimbola

Development Should Embrace Ethnography Already…

… and ditch its poorer but apparently much cuter cousin, RCT. At least that is what I see as the takeaway from this article about external validity problems with RCT – which by the way is similar to the “how do you scale it up” and “how can we apply what you have found in this particular case to other cases” criticism of ethnography. Plus, with ethnography, you get a much, much richer understanding of people’s lives, the choices they make, how they understand those choices – with all those situated in a larger historical and political economic context.

The article is here. Don’t forget to also read the comments.

I wrote about RCT here a couple of years ago. I also wrote a bit about Dean Karlan’s More Than Good Intentions: How a New Economics Is Helping to Solve Global Poverty here.


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A Short Reading List on Economic Informality

A couple of days ago on Twitter I promised to do a short reading list on economic informality. Here goes:

The work that introduced the concept of informal economy:  

Hart, K. (1973). Informal Income Opportunities and Urban Employment in Ghana. The Journal of Modern African Studies, 11(1), 61–89.

See also, Leys, C. (1973). Interpreting African Underdevelopment: Reflections on the ILO Report on Employment, Incomes and Equality in Kenya. African Affairs, 72(289), 419–429

If we must quantify: 

Feige, E. L. (1990). Defining and Estimating Underground and Informal Economies: The new Institutional Economics Approach. World Development, 18(7), 989–1002.

Smith, J. D. (1985). Market Motives in the Informal Economy. In P. D. W. Gaertner & P. D. A. Wenig (Eds.), The Economics of the Shadow Economy (pp. 161–177). Springer: Berlin Heidelberg.

Nkendah, R. (2013). Estimating the informal cross-border trade of agricultural and horticultural commodities between cameroon and its CEMAC neighbours. Food Policy, 41, 133–144.

Loayza, N. V. (1996). The economics of the informal sector: a simple model and some empirical evidence from Latin America. Carnegie-Rochester Conference Series on Public Policy, 45, 129–162.

Thießen, U. (1997). The informal economy in eastern Europe: The example of the Ukraine. Economic Bulletin34(6), 19–24.


Gërxhani, K. (2004). The Informal Sector in Developed and Less Developed Countries: A Literature Survey. Public Choice, 120(3), 267–300.

Castells, M., & Portes, A. (1989). World Underneath: The Origins, Dynamics, and Effects of the Informal Economy. In M. Castells, A. Portes, & L. A. Benton (Eds.), (pp. 11–37). Baltimore: The Johns Hopkins University Press.

Economic anthropology/economic & rural sociology/political economy:

Smith, M. E. (1989). The Informal Economy. In S. Plattner (Ed.), Economic Anthropology (pp. 292–317). Stanford: Stanford University Press

Roitman, J. L. (1990). The Politics of Informal Markets in Sub-Saharan Africa. The Journal of Modern African Studies, 28(4), 671–696.

Pohit, S., & Taneja, N. (2003). Indias Informal Trade with Bangladesh: A Qualitative Assessment. The World Economy, 26, 1187–1214.

Guyer, J. I., & Obukhova, E. (2002). Transcending the Formal/Informal DIstinctino: Commercial Relations in Africa and Russia in the Post 1989 World. In J. Ensminger (Ed.), (pp. 199–220). Walnut Creek: Altamira.

Hart, K. (2006). Bureaucratic form and the informal economy. In R. K. a. E. O. Basudeb Guha-Khasnobis (Ed.), (pp. 21–36). Oxford: Oxford University Press.

Klein, A. (1999). The Barracuda’s Tale: Trawlers, the Informal Sector and a State of Classificatory Disorder off the Nigerian Coast. Africa: Journal of the International African Institute, 69(4), 555–574.

Onokerhoraye, A. G. (1977). Occupational Specialization by Ethnic Groups in the Informal Sector of the Urban Economies of Traditional Nigerian Cities: The Case of Benin. African Studies Review, 20(1), 53–69.

Neef, R. (2002). Aspects of the Informal Economy in a Transforming Country: The Case of Romania. International Journal of Urban and Regional Research, 26(2), 299–322.

Williams, C. C., Round, J., & Rodgers, P. (2007). Beyond the formal/informal economy binary hierarchy. International Journal of Social Economics, 34(6), 402–414.


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On Nigeria’s GDP Rebasing – Plus Links I Find Interesting, Rebasing Edition

There really is nothing much to the rebasing/re-benchmarking exercise. That it has not been done in such a long period, hence making the updated figures sound so huge, says more about governance in Nigeria than anything else. And any serious Nigeria analyst or private sector player is not really surprised by the figures.

The point that jumps at most people is the fact that the new figures show that Nigeria’s economy is the biggest in Africa (really, journalists, analysts, commentators, could you please not add ‘now’ before biggest?). This means that it is bigger than the South African economy. Well, it is a numbers game. Nigeria has more than thrice the population of South Africa, so it shouldn’t be totally surprising that the Nigerian economy is larger than the SA economy by less than USD140b.

What Nigeria gets from this is a morale boost. The FT quotes Dr Okonjo-Iweala, the Coordinating Minister for the Economy, as saying, “The revision will have a psychological impact. It underlines to foreign investors that this country has a large consumer base.” I agree.

What we also get is a new debt-to-GDP ratio that suddenly gives more room for debt – which I personally find scary. Plus we also get a  lower growth rate. Anyways, some links below, for more on the issue.

1. Feyi Fawehinmi wrote this before the new GDP figures were announced – GDP Rebasing and Reality: The Nigerian Story

2. FT – Nigeria almost doubles GDP in recalculation

3. On NigeriansTalk: Ifeanyi Uddin – On The New GDP Numbers; Nonso Obikili – A story about Emeka and GDP rebasing

4. Chuba Ezekwesili – The Bricklayer’s Guide to Understanding Nigeria’s GDP Rebase

5. From Nigeria’s National Bureau of Statistics – FAQs on Nigeria’s GDP Rebasing

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The punishment of an open (Norwegian) prison

Now imagine yourself in a prison that commands a view from a tourist brochure. Your cell phone lies on a shelf, next to a TV and CD player, inside a prison that lets you go to paid work or study. There is no perimeter wall. Prison staff will help you with free-world social services to cover a missed month’s rent on your family’s apartment. Another will help you look for work, or for the next stage of education. Imagine yourself a prisoner who knows he is in prison for what he did, not because of his color or class, or because, lacking the resources for a proper defense, he plea-bargained under threat of near-geological years of incarceration. But also imagine living on this lovely island knowing, every minute of every day, that this is not your home, these people are not your family, your friends, your children, and you are always one misstep from a cell in a closed prison. You have strict curfews. In town you carry an electronic anklet. Yet nothing here feels unfair or unreasonable. You have, after all, committed a crime serious enough to make a range of other remedies untenable. Nothing you can see or touch or smell or taste, and no interaction with staff gives you anything to blame or resent about the system that brought you here.

This is the polished glass nightmare. Every emotional discomfort, every moment of remorse that you might try to cover with resentment of the system, everything you try to grip onto to crawl away from personal responsibility slides back into the pit of the self. Judges and prosecutors are unelected professionals who are under political pressure only tominimize prison populations. The message everywhere you look and walk is the same. You did this to yourself. You sit in a university classroom, but you harbor a secret. You are not like the others. On the way to work, you walk along a lovely sea wall, among kids and adults on holiday, but you know you are not free. You look like them; they never raise an eyebrow at you. But you know. You are under quarantine, and the disease is the past you made for yourself. Everything is being done to help and prepare you to clear this secret and live again like others. But the weight, finally, rests with you. This truly existential weight is implicit in the principle of normality, which is practiced throughout Scandinavian prisons: “The punishment is the restriction of liberty; no other rights have been removed,” reads a fact sheet on criminal services in Norway. “During the serving of a sentence, life inside will resemble life outside as much as possible. You need a reason to deny a sentenced offender his rights, not to grant them. Progression through a sentence should be aimed as much as possible at returning to the community. The more closed a system is, the harder it will be to return to freedom.”

In full in The Atlantic.

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*Scientists like to think of science as self-correcting. To an alarming degree, it is not*

From The Economist:

Academic scientists readily acknowledge that they often get things wrong. But they also hold fast to the idea that these errors get corrected over time as other scientists try to take the work further. Evidence that many more dodgy results are published than are subsequently corrected or withdrawn calls that much-vaunted capacity for self-correction into question. There are errors in a lot more of the scientific papers being published, written about and acted on than anyone would normally suppose, or like to think.

Various factors contribute to the problem. Statistical mistakes are widespread. The peer reviewers who evaluate papers before journals commit to publishing them are much worse at spotting mistakes than they or others appreciate. Professional pressure, competition and ambition push scientists to publish more quickly than would be wise. A career structure which lays great stress on publishing copious papers exacerbates all these problems. “There is no cost to getting things wrong,” says Brian Nosek, a psychologist at the University of Virginia who has taken an interest in his discipline’s persistent errors. “The cost is not getting them published.”

First, the statistics, which if perhaps off-putting are quite crucial. Scientists divide errors into two classes. A type I error is the mistake of thinking something is true when it is not (also known as a “false positive”). A type II error is thinking something is not true when in fact it is (a “false negative”). When testing a specific hypothesis, scientists run statistical checks to work out how likely it would be for data which seem to support the idea to have come about simply by chance. If the likelihood of such a false-positive conclusion is less than 5%, they deem the evidence that the hypothesis is true “statistically significant”. They are thus accepting that one result in 20 will be falsely positive—but one in 20 seems a satisfactorily low rate.

In full here.

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