African poverty falling faster than you think

Measuring African poverty

In recent research (Pinkovskiy and Sala-i-Martin 2010), we utilize the methodology of our previous paper (Pinkovskiy and Sala-i-Martin 2009), to mix the typical Penn World Tables GDP series with a thorough inequality database to estimate African income distribution for the time 1970-2006. For countries and years with inequality data, we compute the distribution of income by fitting a lognormal distribution to the inequality data, whereas for countries and years without inequality data, we interpolate inequality based on neighbouring years. If a country does not have any inequality data for the sample period, we interpolate based on the average inequality of countries with inequality data.

Figure 1 presents our main result:

  • Using the $1/day definition of poverty adopted by the Millennium Development Goals, African poverty declined strikingly, from 41.6% in 1990 to 31.8% in 2006 1 .
  • Poverty appears to co-move with GDP almost perfectly.
  • African inequality in addition has fallen over this era, almost entirely reversing its rise since 1970, but nonetheless remaining at a higher absolute level (Figure 2).

Figure 1. African poverty and growth

Figure 2. African inequality

Thus, over positive and sustained African growth (1995 to 2006), not merely did inequality not neglect to explode as could have been the case if all of the growth visited a narrow elite, nonetheless it actually declined substantially.

Our estimates of African inequality allow us to measure African welfare, e.g. by Amartya Sen’s (1976) index of GDP-per-capita x1 without the Gini coefficient. African welfare declined substantially between 1970 and 1995, however the trend was reversed dramatically between 1995 and 2006 (Figure 3). In this decade however, both the different parts of the index moved in the same direction. Mean income increased and overall inequality declined. Hence, African welfare improved.

Figure 3. African welfare (using the Sen measure)

Implications for the Millennium Development Goals

Tables inside our working paper show the expected decline in poverty by 2015 if present trends continue, and the expected date of attainment of the goals for the baseline estimation method and multiple variations to the estimation procedure. We consider alternative ways of extrapolation, distributional assumptions apart from the lognormal, an “adjusted” approach to fitting distributions to the info that makes only use of data in the center of the income distribution that needs to be less suffering from survey misreporting, recovering the distribution by inverting the Gini coefficient, and using other resources of GDP aside from the Penn World Tables. The info published by Angus Maddison and the World Bank’s calculations of GDP following its revision of buying power parity estimates in 2007.

We also think about what happens if the eight largest African countries is dropped from the analysis. We see that Africa will most likely halve poverty in accordance with 1990 sometime between 2015 and 2020, with the baseline estimate being 2017; a couple of years late in accordance with the Millennium Development Goal target. However, being truly a few years late to attain the goal is way better than not making progress towards it at all. The point is that Africa has been relocating the proper direction and, while progress is not as substantial and spectacular as in Asia, poverty has been falling and it’s been falling substantially. We have to not allow literal interpretation of the Millennium goals turn very good news (Africa is rapidly relocating the proper direction) into bad news (Africa won’t achieve the goals promptly) (Easterly 2009).

One reason the Millennium goals are projected to be performed several years late may be the poor performance of the Democratic Republic of Congo (DRC) during the last decade. Naturally, this poor economic performance is due to the war that occurred in that country throughout that decade, and which is currently drawing to a close. If we exclude the DRC from our baseline computation, Africa halves poverty by 2012, 3 years in advance. (For more extensive robustness checks for the scenario without the DRC, see our paper; these show that for some of nations, the MDG is in fact achieved prior to the 2015 target date.)

Why Africa is held back

It has often been suggested that geography and history matter significantly for the power of UNDER-DEVELOPED, and especially African, countries to grow and reduce poverty. Collier (2006) argues that coastal countries, or countries that are mineral-rich, will perform much better than landlocked and mineral-poor countries generally. Bloom and Sachs (1998) indicate adverse geography as a reason behind slow development: specifically, countries which have unfavourable agriculture ought to be poorer than countries with an increase of favourable conditions.

Others have suggested that troubled history may have a persistent influence on growth performance. Nunn (2007 and 2008), for instance, argues that the African slave trade had “particularly detrimental consequences, including social and ethnic fragmentation, political instability and a weakening of states, and the corruption of judicial institutions,” which led the elements of Africa most suffering from the slave trade to grow much slower compared to the parts which were not. La Porta et al. (1999) claim that the identity of the coloniser mattered substantially for development. Since these factors are permanent (and can’t be changed with good policy), they imply some elements of Africa could be at a persistent growth disadvantage in accordance with others.

Yet Figures 4-9 show that the African poverty decline has occurred ubiquitously, in countries which were slighted aswell as in the ones that were favoured by geography and history. For each and every breakdown discussed above, the left panel of the corresponding Figure shows GDP in countries to each side of the breakdown, as the right panel shows poverty rates. As the degrees of the poverty series begin matching the hypotheses lay out above, the poverty rates for countries on either side of the breakdown have a tendency to converge, with the disadvantaged countries reducing poverty significantly to catch up to the advantaged ones. Neither geographical nor historical disadvantages appear to be insurmountable obstacles to poverty reduction.

Figure 4. Landlocked vs. coastal countries

Figure 5. Mineral-rich vs. mineral-poor countries

Figure 6. Landlocked vs. coastal mineral-poor countries

Figure 7. Favourable vs. unfavourable environment for agriculture

Figure 8. Aftereffect of slavery

Figure 9. Colonial origins


Our main conclusion is that Africa is reducing poverty, and carrying it out considerably faster than many thought.

  • The growth from the time 1995-2006, definately not benefiting only the elites, has been sufficiently widely spread that both total African inequality and African within-country inequality actually declined over this era.
  • The speed of which Africa has reduced poverty since 1995 puts it on the right track to attain the Millennium Development Goal of halving poverty in accordance with 1990 by 2015 promptly or, at worst, a year or two late.
  • If the Democratic Republic of Congo converges to the African trend once it really is stabilised, the MDG will be performed by 2012, 3 years prior to the target date.

We also find that the African poverty reduction is remarkably general.

  • African poverty reduction can’t be explained by a big country, as well as by a single group of countries possessing some beneficial geographical or historical characteristic.
  • All classes of countries, including people that have disadvantageous geography and history, experience reductions in poverty.

This observation is specially important because it demonstrates poor geography and history have not posed insurmountable obstacles to poverty reduction.

The lesson we draw is basically optimistic – even the most blighted elements of the poorest continent can set themselves firmly on the trend of limiting and even eradicating poverty within the area of ten years.


Bloom, David E, and Jeffrey D Sachs (1998), “Geography, Demography, and Economic Growth in Africa”, Brookings Papers on Economic Activity, 2:207-273.

Collier, Paul (2006), “Africa: Geography and Growth”, Journal TEN, Federal Reserve Bank of Kansas City, Fall.

Easterly, William (2009), “The way the Millennium Development Goals are Unfair to Africa”, World Development, January.

The Economist (2010), “Uncaging the Lions”, 10 June.

La Porta, Rafael, Florencio Lopez de Silanes, Andrei Shleifer and Robert Vishny (1999), “The standard of Government”, Journal of Law, Economics and Organization, 15(1):222-79

Nunn, Nathan (2008), “The Long-Term Ramifications of Africa’s Slave Trades”, Quarterly Journal of Economics, 123(1):139-176.

Pinkovskiy, Maxim and Xavier Sala-i-Martin (2009), “Parametric Estimations of the World Distribution of Income”, NBER Working Paper 15433

Pinkovskiy, Maxim and Xavier Sala-i-Martin (2010), “African Poverty is Falling. CONSIDERABLY FASTER than YOU IMAGINE!”, NBER Working Paper 15775.

Ravallion, Martin (2010), “Is African poverty falling?”,, 3 May.

1 Martin Ravallion (2010) argues that the poverty line ought to be defined using consumption instead of income, and that greater weight ought to be positioned on poverty counts instead of poverty rates. However, we consider our definition of poverty is in keeping with the one utilized by the Millennium Development Goals. See our response to Ravallion here.

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