Comments on: Is African poverty falling faster than we think?

By: Jeffrey Maganya

Jeffrey Maganya — Tue, 16 Mar 2010 06:38:13 +0000

The diversity and differences in Africa, especially in relation to incomes can be so wide as to make statistical generalities meaningless. I guess the answers to some of the questions that beg for more quantitative information than we can get lies on development/increased use of more vigorous qualitative methods.

The problem with poverty analyses in Africa is that while the vast array of poverty students are providing answers we have have yet to pose the right questions and use Africa-specific definitions and methodologies. An example is if you were to look at Kenya the life expectancy at birth is 57.86 Years. Now look at infant mortality rate which is 54.7 deaths/1,000 live births. Any person who crosses age five suddenly has a much higher chance of living to over 70 years. Before one reached 35 years HIV and AIDS takes it toll. The life expectancy of one who lives to over 35 is then presumably much higher. Various regions in Kenya also have extreme differences. In Siaya District alone in Kenya the infant mortality rates range 80 to 200 per 1,000 births. And all these data have to be taken with a pinch of salt. With all these age, gender, geographical, ethnic and other variations; and with inability to collect sensible data within this diversity, national statistics seem rather hollow, save for the fact that is is used by most national, international authorities to define priorities. I think that the time to pose questions about descriptions and methodological issues is now. So far we have gotten rights statistical answers to the wrong questions…

By: bertha

bertha — Thu, 11 Mar 2010 13:25:07 +0000

Come live with us in the village for for 3 months and then analyse your claims.

By: Paul Atherton

Paul Atherton — Tue, 09 Mar 2010 13:16:44 +0000

The PWT are notably inconsistent between vintages. Pretty much any model selection methodology in a growth context (ala Sala-i-Martin, Doppelhoffer etc.) yields different conclusions dependent on which dataset you use. Could partly explain why the growth literature is so inconsistent. I’ve a paper under review which shows just this, but guess it’ll get rejected on the grounds that i’m not Simon Johnson ;o)

By: Scott

Scott — Tue, 09 Mar 2010 08:57:45 +0000

See Pogge and Reddy on global poverty measurement, which they (correctly) argue is unknown. http://www.socialanalysis.org. Both Sala-i-Martin and Ravallion are using a flawed and conceptually unclear idea of what poverty is, then using data that is not comparable across contexts of over time, at a poverty line that is unjustified. Absent information on the costs of the smaller basket of goods consumed by the poor, both estimates are meaningless. Even if that information were available, we still would only be calculating poverty in the narrow sense of sufficient income to cover a small cost of goods, excluding multidimensional deprivations that almost everyone now recognize as a necessary part of any plausible analysis of poverty.

By: Mona

Mona — Mon, 08 Mar 2010 23:06:20 +0000

As someone who, another lifetime ago, worked on the World Development Indicators, I can corroborate the claims in that last paragraph!

By: Adam

Adam — Mon, 08 Mar 2010 15:38:56 +0000

Prejudice is making a statement before considering the facts. I think the facts are quite clear here.

By: Justin Kraus

Justin Kraus — Mon, 08 Mar 2010 13:36:28 +0000

Not really. Its just a recognition that low income countries almost never have the resources to adequately gather data.

By: Little Bird

Little Bird — Mon, 08 Mar 2010 13:26:18 +0000

“Second, never, ever take data from low income countries too seriously.”

This sentence shows a little bit of prejudice, doesn’t it?